Clinical relevance of low-density Plasmodium falciparum parasitemia in untreated febrile children: A cohort study

Mary-Anne Hartley; Natalie Hofmann; Kristina Keitel; Frank Kagoro; Clara Antunes Moniz; Tarsis Mlaganile; Josephine Samaka; John Masimba; Zamzam Said; Hosiana Temba; Iveth Gonzalez; Ingrid Felger; Blaise Genton; Valérie D’Acremont

doi:10.1371/journal.pmed.1003318

. 2020 Sep 21;17(9):e1003318. doi: 10.1371/journal.pmed.1003318

Clinical relevance of low-density Plasmodium falciparum parasitemia in untreated febrile children: A cohort study

Mary-Anne Hartley ^1,^2,^*, Natalie Hofmann ³, Kristina Keitel ³, Frank Kagoro ⁴, Clara Antunes Moniz ³, Tarsis Mlaganile ⁴, Josephine Samaka ^4,⁵, John Masimba ⁴, Zamzam Said ⁴, Hosiana Temba ⁴, Iveth Gonzalez ⁶, Ingrid Felger ³, Blaise Genton ^1,³, Valérie D’Acremont ^1,³

Editor: Lorenz von Seidlein⁷

PMCID: PMC7505590 PMID: 32956354

Abstract

Background

Low-density (LD) Plasmodium infections are missed by standard malaria rapid diagnostic tests (standard mRDT) when the blood antigen concentration is below the detection threshold. The clinical impact of these LD infections is unknown. This study investigates the clinical presentation and outcome of untreated febrile children with LD infections attending primary care facilities in a moderately endemic area of Tanzania.

Methods/findings

This cohort study includes 2,801 febrile pediatric outpatients (median age 13.5 months [range 2–59], female:male ratio 0.8:1.0) recruited in Dar es Salaam, Tanzania between 01 December 2014 and 28 February 2016. Treatment decisions were guided by a clinical decision support algorithm run on a mobile app, which also collected clinical data. Only standard mRDT+ cases received antimalarials. Outcomes (clinical failure, secondary hospitalization, and death) were collected in follow-up visits or interviews on days 3, 7, and 28. After patient recruitment had ended, frozen blood from all 2,801 patients was tested for Plasmodium falciparum (Pf) by ultrasensitive–quantitative polymerase chain reaction (qPCR), standard mRDT, and “ultrasensitive” mRDT. As the latter did not improve sensitivity beyond standard mRDT, it is hereafter excluded. Clinical features and outcomes in LD patients (standard mRDT-/ultrasensitive-qPCR+, not given antimalarials) were compared with those with no detectable (ND) parasitemia (standard mRDT-/ultrasensitive-qPCR-) or high-density (HD) infections (standard mRDT+/ultrasensitive-qPCR+, antimalarial-treated).

Pf positivity rate was 7.1% (n = 199/2,801) and 9.8% (n = 274/2,801) by standard mRDT and ultrasensitive qPCR, respectively. Thus, 28.0% (n = 76/274) of ultrasensitive qPCR+ cases were not detected by standard mRDT and labeled “LD”. LD patients were, on average, 10.6 months younger than those with HD infections (95% CI 7.0–14.3 months, p < 0.001). Compared with ND, LD patients more frequently had the diagnosis of undifferentiated fever of presumed viral origin (risk ratio [RR] = 2.0, 95% CI 1.3–3.1, p = 0.003) and were more often suffering from severe malnutrition (RR = 3.2, 95% CI 1.1–7.5, p = 0.03). Despite not receiving antimalarials, outcomes for the LD group did not differ from ND regarding clinical failures (2.6% [n = 2/76] versus 4.0% [n = 101/2,527], RR = 0.7, 95% CI 0.2–3.5, p = 0.7) or secondary hospitalizations (2.6% [n = 2/76] versus 2.8% [n = 72/2,527], RR = 0.7,95% CI 0.2–3.2, p = 0.9), and no deaths were reported in any Pf-positive groups. HD patients experienced more secondary hospitalizations (10.1% [n = 20/198], RR = 0.3, 95% CI 0.1–1.0, p = 0.005) than LD patients. All the patients in this cohort were febrile children; thus, the association between parasitemia and fever cannot be investigated, nor can the conclusions be extrapolated to neonates and adults.

Conclusions

During a 28-day follow-up period, we did not find evidence of a difference in negative outcomes between febrile children with untreated LD Pf parasitemia and those without Pf parasitemia. These findings suggest LD parasitemia may either be a self-resolving fever or an incidental finding in children with other infections, including those of viral origin. These findings do not support a clinical benefit nor additional risk (e.g. because of missed bacterial infections) to using ultrasensitive malaria diagnostics at a primary care level.

Mary-Anne Hartley and colleagues investigate the clinical consequences of untreated low-density parasitaemia that is only detectable with ultrasensitive malaria tests.

Author summary

Why was this study done?

Every infection has a symptomatic threshold, above which the magnitude of infection burden triggers fever and other clinical symptoms that distinguishes ill individuals from those who remain asymptomatic. In malaria, this is called the “pyrogenic (fever) threshold.”
The standard malaria rapid diagnostic tests (sd-mRDTs), which have been in use for decades, can detect parasite loads of up to 10-fold below this threshold.
New ultrasensitive malaria tests are now able to detect genetic traces of Plasmodium parasites that go 1,000-fold further.
However, the clinical relevance of these minute levels of parasitemia is unknown.
Does it detect a previously unappreciated cause of clinical failure? Or does it risk reporting a clinically irrelevant signal that may distract the clinician from other causes of fever?

What did the researchers do and find?

We assessed the clinical consequences of untreated low-density (LD) parasitemia that is only detectable with the ultrasensitive malaria test.
In a cohort of 2,801 pediatric outpatients in Tanzania, we observed that of all patients in whom parasites were detected using ultrasensitive tests, over a quarter were not detected by standard mRDTs.
However, despite not receiving antimalarials, patients with LD parasitemia did not differ from those without any detectable parasites regarding clinical outcomes during a 28-day follow-up.

What do these findings mean?

These findings suggest LD parasitemia may either be a self-resolving fever or an incidental finding in children with other infections.
These findings neither support a specific utility nor risk (other than the obvious wasted resources) to using ultrasensitive malaria diagnostics at a primary care level.

Introduction

The presence of Plasmodium parasites in the blood of a febrile patient does not necessarily imply causality. Low-density (LD), asymptomatic carriage of Plasmodium parasites is often more common than clinical malaria itself and may circulate in as many as 80% of individuals in highly endemic areas [1]. Indeed, the average parasitemia at which malaria-specific fever develops (known as the pyrogenic threshold) is estimated to be well over 50 parasites per microliter of blood [2]. LD infections are often below the detection threshold of standard malaria rapid diagnostic tests (standard mRDTs) and microscopy (at ±50 parasites/μl) [3–5]. Although these undiagnosed infections have the potential to serve as a reservoir for transmission [1], their impact on short- and long-term health outcomes is unknown. The utility and safety of detecting and/or treating such potentially harmless infections in febrile patients must still be evaluated.

Molecular diagnostic tools such as ultrasensitive quantitative polymerase chain reaction (ultrasensitive qPCR) are able to detect genetic traces of Plasmodium falciparum (Pf) parasites corresponding to infection densities as low as 0.03 parasites/μl [6], an over 1,000-fold improvement from the average 100–200 parasites/μl limit of standard mRDTs [7]. However, PCR-based testing requires trained personnel, well-equipped laboratories and other resources that are not always available in endemic areas. In response to this problem, a new easy-to-use and affordable “ultrasensitive” mRDT was developed (Alere, Abbott Diagnostics) able to detect the Pf histidine-rich protein-2 (HRP-2) with 10-fold greater sensitivity to that of standard mRDTs [8]. Our group, however, has reported only marginal improvements on sensitivity using ultrasensitive qPCR as a gold standard (75% versus 73%) [6]. It should be appreciated, however, that as HRP-2 is an inert protein component of Pf parasites, detection methods using HRP-2 are thus limited as proxy measures of parasitemia, in which thresholds of detection may vary greatly. Indeed, WHO-certified standard mRDTs are able to detect infections at approximately 200 parasites/ul but may be more sensitive in practice. So far, the ultrasensitive mRDTs have been trialed in various community surveys to assess Pf prevalence, but the clinical impact of such sensitive diagnostic tools has not yet been evaluated on symptomatic patients at the health facility level (where most patients with malaria are diagnosed).

As many of the LD infections are also asymptomatic, these highly sensitive tests challenge Koch’s postulates of what defines a “pathogen” and at what concentration should a detected parasite be considered “disease-causing,” necessitating the implementation of preventive or therapeutic interventions. It thus becomes important to assess at which point this gain in sensitivity surpasses its clinical benefit, perhaps even becoming counterproductive: where the detection of incidental Pf parasitemia in a febrile child may distract clinicians from diagnosing other serious and treatable coinfections such as bacterial sepsis or meningitis. A recent WHO assessment of the potential use of ultrasensitive mRDTs concluded that more studies are needed to evaluate the potential risk of missed diagnosis and treatment of serious illness following the identification of LD Pf infections and the potential benefits of detection and treatment of LD infections [7]. Currently, the WHO guidelines on the Integrated Management for Childhood Illnesses (IMCI) only recommend antimalarial treatment in the presence of a positive standard mRDT result [9]. Thus far, this strategy has proven to be safe in clinical practice and has considerably improved case management and rational use of antimalarial drugs both in endemic environments [10, 11] and in travelers (in whom parasite densities are typically lower) [12]. Because of the successful experience with standard mRDTs and their wide margin of safety, more sensitive methods are not being promoted for routine use in febrile case management.

To our knowledge, this is the first study to assess the clinical benefit and potential risk of using ultrasensitive malaria diagnostics at a primary care level in febrile children.

These analyses aim to fill gaps in policy recommendations that were highlighted by the WHO technical committee regarding the use of highly sensitive point-of-care Pf malaria diagnostics. We report the prevalence and clinical presentation of LD parasitemia detectable only by ultrasensitive tools such as ultrasensitive qPCR and ultrasensitive mRDT and evaluate its impact on clinical outcomes in a cohort of febrile children in a setting of moderate malaria endemicity.

Materials and methods

Design

Patient population and context

This secondary cohort analysis investigates data collected from 3,192 children (aged 2–59 months) with acute febrile illness (axillary temperature ≥37.5°C for ≤7 days) recruited at 9 primary care outpatient clinics in Dar es Salaam, Tanzania between December 2014 and February 2016. The data were originally collected as part of a randomized controlled, noninferiority study to compare the clinical outcome of children using clinical decision support algorithms for the management of acutely ill children (e-POCT and ALMANACH) [13]. During the trial, the blood samples were collected for a prospective subcohort study investigating the etiologies and clinical relevance of nonmalarial febrile disease. The protocol for this trial was previously published here:

https://doi.org/10.1371/journal.pmed.1002411.s010. The details of which molecular tests would be used to elucidate infectious etiology from the biological samples were decided after the trial had concluded. Repeated malaria testing on blood samples was required after local health authorities reported suboptimal specificity of a single lot of standard mRDTs used onsite [14]. mRDTs as well as more sensitive methods of qPCR and “ultrasensitive” mRDTs were used to verify results. This study reports the clinical relevance of discrepancies between these test results.

All patients were assessed and managed using the electronic clinical decision support algorithms e-POCT [13] and ALMANACH [15], which offer diagnostic and treatment guidance derived from the WHO IMCI guidelines [9]. These IMCI-derived algorithms are designed to guide clinicians through a structured consultation and recommend appropriate treatment predicted from the systematically collected data, including integrated point-of-care tests. No significant differences were noted between e-POCT and ALMANACH trial arms regarding the distribution of the outcomes or subcohorts studied.

Regarding malaria, all children were tested by standard mRDT; positive cases were treated with an antimalarial treatment, whereas negative cases were not given antimalarials.

Aims

The present study was designed to compare clinical outcomes between patients with untreated LD Pf parasitemia to those with no detectable (ND) parasites or those treated for high-density (HD) infection. We (1) measure the prevalence and distribution of LD parasitemia, (2) describe the clinical presentation of LD infection, and (3) investigate the impact of LD infection on clinical outcomes up to day 28.

Clinical data and data collection

Data were thus collected via systematic clinical questionnaires embedded in a mobile app and included (1) demographic information (age, sex, region, date of consultation, etc.); (2) relevant medical history (HIV status, antibiotic or antimalarial consumption in the past 7 days, history of chronic illness, etc.); and (3) presence, severity, and duration of symptoms (fever, pain, or specific complaints of the respiratory, gastrointestinal, neurological, or dermatological system).

During the consultation, clinical signs of a relevant focused examination were also recorded (vital and danger signs, temperature, respiratory rate, malnutrition assessment, etc.) along with laboratory tests recommended by the app (mRDT, C-reactive protein [CRP], hemoglobin, urinary dipstick, etc.). The app then used this entered information to generate diagnoses (pneumonia, upper respiratory tract infection, malaria, presumed viral illness, etc.).

Finally, follow-up was performed physically at days 3 and 7 (except for children entirely cured at day 3 who were followed by telephone at day 7) and telephonically at day 28, to perform a follow-up assessment and management, if needed, and collect clinical outcomes (clinical failure, secondary hospitalization, or death). A physical visit was organized if the telephonic questionnaire revealed evidence of clinical failure. No patients were lost to follow-up in the subgroup of children included in the present analysis. The mobile algorithms are described in detail in the original paper [13]).

Laboratory procedures

Pf detection

In order to ensure comparability of malaria tests, frozen whole blood samples were retested under standard laboratory conditions in Switzerland for the presence of P. falciparum after patient recruitment had ended. This included the 2 rapid tests: standard mRDTs (Malaria Ag Pf, Abbott Diagnostics; reference 05FK50; lot 05CDB228A) and ultrasensitive mRDT (Alere Malaria Ag Pf, Abbott Diagnostics; reference 05FK140; lot 05LDB004A), as previously described [14]. These rapid tests both targeted the HRP-2 antigen, the presence of which was verified in a previous study [14]. The ultrasensitive qPCR approach (described previously [14]) targeted the conserved C-terminal region of the multiple-copy var gene family, which has a limit of detection of <0.1 parasites per μL of blood [6]. As the ultrasensitive mRDT did not improve sensitivity beyond standard mRDT, it is excluded from further analyses.

Exposures and outcomes

Exposures

The malaria test results were used to divide the population into 3 subgroups: (1) HD Pf infection (detected by standard mRDT and confirmed by ultrasensitive qPCR), (2) LD Pf infection (ultrasensitive-qPCR+ samples that are not detectable by standard mRDT), or (3) not detectable by all available methods (ND) (Table 1). The administration of antimalarial treatment was based solely on the result of the standard mRDT performed on site at presentation and was thus given to children in the HD group. Children with medium-density (MD) Pf infection (ultrasensitive qPCR+ and ultrasensitive mRDT+ but standard mRDT-) could not be analyzed separately because of their low number (n = 3). Results of ultrasensitive mRDTs are presented in the supplement (S1 Table).

Table 1. Definition of the 3 subcohorts based on Pf parasitemia level and treatment received.

		Malaria test results		Received antimalarials
		Standard mRDT	Ultrasensitive qPCR	Received antimalarials
Positive control	HD Pf parasitemia	+	+	Yes
Negative control	ND Pf parasitemia	−	−	No
Cases of interest	LD Pf parasitemia	−	+	No

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HD, high-density; LD, low-density; mRDT, standard rapid diagnostic test; ND, no detectable; qPCR, quantitative polymerase chain reaction.

Outcomes

As described previously, morbidity and mortality outcomes were collected in follow-up visits or interviews at 3-, 7-, and 28-days postconsultation. Primary outcomes were the proportion of clinical failures (development of severe symptoms, significant dehydration or clinical pneumonia on/after day 3, or persistent symptoms at day 7) and severe adverse events (secondary hospitalizations, conversion to HD infection, and deaths) by day 28. Associations with clinical variables (signs/symptoms, diagnoses, and laboratory results) were also assessed.

Some exposures and outcomes are classified with levels of severity, and their definitions are tabulated in S2 Table along with the definition of clinical failure.

Statistical analyses

Analyses were performed in Stata15 (SE, StataCorp, https://www.stata.com/) and presented using Prism 8 (GraphPad, https://www.graphpad.com/scientific-software/prism/).

Epidemiology of Pf infection

HD, LD, and ND are described in terms of prevalence and distribution across key demographic variables (age, sex, season). Fitted fractional polynomial plots were used to visualize predicted probabilities of each parasite density group across age.

Clinical presentation of Pf infection

The presence of clinical signs/symptoms as well as laboratory measures and final diagnoses in the LD group were compared with ND and HD (Table 1). Relative prevalence and bivariate analysis are reported as percentages and risk ratios (RRs) with p-values and confidence intervals. Logistic regression and chi-squared analyses were used. Risk ratios were obtained according to Zhang and Yu [16].

Clinical outcomes

Clinical outcomes in patients with LD infections were compared with ND and HD groups as described previously. This study primarily focused on comparisons between LD and ND groups, both of whom were not treated with antimalarials: A difference in outcomes between these groups would hence indicate LD Pf parasitemia-attributable morbidity. Dose-dependency of outcomes and presentations was also investigated using the parasite density estimated by ultrasensitive-qPCR. Logistic regression and chi-squared analyses were used as described previously.

Controlling for bias

Age, seasonality, and malnutrition have known independent associations with both Pf infection and the outcomes of interest; these parameters were controlled for confounding where appropriate and indicated whenever reported.

Missing values

All missing data in variables used for analyses are indicated as absolute values in Tables 3–5. In general, missing values were generated because of the resource-conserving and clinical logic of the algorithms in the mobile app (i.e., not performing a certain test if the patient did not fulfil the pretest risk assessment criterion/a that would indicate the necessity of the test). For instance, hemoglobin was only measured in the 51% of patients with a clinical suspicion of anemia (n = 1,374/2,801 missing). Similarly, sickle cell anemia was only tested in 37% of the cohort (n = 1,773/2,801 missing). HIV test results were missing from 8.5% of the cohort (n = 237/2,801 missing) and district was missing in 4% of the cohort (n = 110/2,801). Missing values were missing at random according to the 3 subgroups (LD, HD, ND) and were thus excluded from analyses.

Table 3. Comparative analysis of demographic and epidemiological features (ND versus LD).

	ND (Undetectable) sd-mRDT-/us-qPCR-		LD parasitemia sd-mRDT-/us-qPCR+		LD versus ND parasitemia
	Prevalence				Crude bivariate analysis				Adjusted (Season)
Total	%	Prevalence	%	Prevalence
n = 2,801	90.2	2527/2801	2.7	76/2801
Demographics	Median	IQR	Median	IQR	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Age (months)	13.0	(8.3–21.7)	13.1	(8.4–21.0)	1.0	(1.0–1.0)	0.9		1.0	(1.0–1.0)	0.7
	%	Total = 2,527	%	Total = 76	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Sex (female)	44.3	1,120	50.0	38	1.3	(0.8–2.0)	0.3		1.3	(0.8–2.0)	0.3
Season (post rainy)	50.5	1,275	81.6	62	4.2	(2.4–7.2)	<0.001	^a	--> Potential confounder
District (Kinondoni)	60.2	1,457/2,422	57.7	41/71	0.9	(0.6–1.4)	0.7		1.2	(0.7–1.9)	0.5
District (Temeke)	32.1	778/2,422	42.3	30/71	1.5	(1.0–2.4)	0.07		1.0	(0.6–1.7)	0.8
District (Ilala)	7.7	187/2,422	0.0	0/71	–	–	–		–	–	–
Treatment exposure	%	Total = 2,527	%	Total = 76	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Antimalarials	0.0	0	0.0	0	–	–	–		–	–	–
Antibiotics	20.7	523	15.8	12	0.7	(0.4–1.3)	0.3	^a	0.8	(0.5–1.5)	0.6

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Low-density (LD: sd-mRDT-/us-qPCR+) versus undetectable Pf parasitemia (ND: sd-mRDT-/us-qPCR-).

HD, high-density Pf infection; LD, low-density Pf infection; RR, risk ratio; RR_adj; adjusted RR; RR_crude, crude (unadjusted) RR; sd-mRDT, standard malaria rapid diagnostic test; us-qPCR, ultrasensitive quantitative PCR.

^ap < 0.05 and considered as statistically significant.

Table 5. Comparative analysis of clinical presentation, lab results, and diagnoses at day zero.

LD versus ND (low-density versus undetectable)

	ND (Undetectable) sd-mRDT-/us-qPCR-		LD parasitemia sd-mRDT-/us-qPCR+		LD versus ND parasitemia
	Prevalence				Crude bivariate analysis				Adjusted (season)
Signs and symptoms	%	Total = 2,527	%	Total = 76	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Danger signs present	1.3	34	1.3	1	1.0	(0.1–6.1)	1.0		1.4	(0.2–8.1)	0.8
Respiratory distress	7.1	180	1.3	1	0.2	(0.0–1.2)	0.08		0.4	(0.1–2.6)	0.3
Cough	59.1	1,493	39.5	30	0.5	(0.3–0.7)	0.001	^a	0.5	(0.3–0.8)	0.003	^a
Pharyngitis	1.4	36	1.3	1	0.9	(0.1–5.8)	0.9		1.1	(0.1–6.6)	0.9
Abdominal pain	4.1	103	6.6	5	1.6	(0.7–3.8)	0.3		1.5	(0.6–3.6)	0.4
Loss of appetite	2.3	58	3.9	3	1.7	(0.5–5.0)	0.4		1.9	(0.6–5.4)	0.3
Vomit	19.1	483	26.3	20	1.5	(0.9–2.4)	0.1		1.3	(0.8–2.2)	0.3
Diarrhea	17.3	438	14.5	11	0.8	(0.4–1.5)	0.5		0.8	(0.4–1.4)	0.4
Fever only	13.1	332	13.2	10	1.0	(0.5–1.9)	1.0		1.0	(0.5–1.9)	1.0
FWS^b	29.8	753	43.4	33	1.8	(1.1–2.7)	0.01	^a	1.7	(1.1–2.6)	0.03	^a
Lab results and measures	Mean	CI95%	Mean	CI95%	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Temperature (°C)	38.3	(38.3–38.3)	38.3	(38.1–38.5)	1.0	(0.7–1.5)	0.8		1.1	(0.8–1.5)	0.7
Preconsult fever duration	1.5	(1.4–1.5)	1.3	(1.1–1.5)	0.8	(0.6–1.1)	0.1		0.9	(0.6–1.1)	0.3
Hemoglobin (g/dL)	9.7	(9.7–9.8)	9.6	(9.2–10.1)	0.9	(0.8–1.2)	0.6		0.9	(0.8–1.2)	0.6
	Median	IQR	Median	IQR	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
CRP (mg/L)	0.0	(0.0–10.0)	0.0	(0.0-10.0)	1.0	(1.0–1.0)	0.7		1.0	(1.0–1.0)	0.9
PCT (ug/L)	0.2	(0.1–0.6)	0.3	(0.1-0.4)	0.9	(0.8–1.1)	0.5		0.9	(0.8–1.1)	0.4
Diagnoses	%	Total = 2,527	%	Total = 76	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Anemia (moderate-to-severe)^c	54.8	700/1,277	56.5	26/46	1.0	(0.6–1.9)	0.8		1.0	(0.6–1.8)	0.9
Sickle cell disease (HbSS)^d	1.8	16/895	0.0	0/40	0.6	(0.2–1.6)	0.3		0.6	(0.2–1.7)	0.4
Sickle cell trait (HbAS)^d	13.9	124/895	10.0	4/40	0.6	(0.2–1.6)	0.3		0.6	(0.2–1.7)	0.4
Malnutrition	7.2	181	9.2	7	1.3	(0.6–2.7)	0.5		1.4	(0.6–2.9)	0.4
Severe malnutrition	1.7	43	5.3	4	3.0	(1.1–7.5)	0.03	^a	3.0	(1.1–7.5)	0.03	^a
Severe illness	5.6	142	11.8	9	2.2	(1.1–4.0)	0.02	^a	2.6	(1.3–4.8)	0.01	^a
URTI	13.2	331/2,503	13.3	10	1.0	(0.5–1.9)	1.0		1.0	(0.5–1.8)	0.9
Pneumonia	26.8	678	13.2	10	0.4	(0.2–0.8)	0.01	^a	0.5	(0.3–1.0)	0.04	^a
HIV	1.4	33/2,311	1.5	1/68	1.0	(0.1–6.4)	1.0		1.6	(0.2–9.3)	0.6
Suspected viral infection	25.9	655	42.1	32	2.1	(1.3–3.1)	0.002	^a	1.9	(1.2–2.9)	0.01	^a
Suspected bacterial infection	4.0	102	1.3	1	0.3	(0.1–2.2)	0.3		0.3	(0.1–2.3)	0.3

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^ap < 0.05 and considered as statistically significant

^bFWS is diagnosed using sd-mRDT, and it is thus not present in HD infection.

^cModerate-to-severe anemia: Hb < 9 g/dL.

^dHbSS only investigated in samples with sufficient blood volume (i.e., 40/78 LD, 87/198 HD, and 895/2,527).

^eCRP was measured using a categorical quantitation test. Four categories exist: <10 mg/L, 10–40 mg/L, 40–80 mg/L, and >80 mg/L. The lower limit of this range is represented in the table. See S2 Table for the definition of severe illness and severe malnutrition.

CRP, C-reactive protein; FWS, fever without source; HbAS heterozygote, sickle cell trait; HbSS homozygote, sickle cell disease; HD, low-density Pf infection; HIV, human immunodeficiency virus; LD, low-density Pf infection; PCT, procalcitonin; RR, risk ratio; RR_adj, adjusted RR; RR_crude, crude (unadjusted) RR; Sd-mRDT, standard malaria rapid diagnostic test; URTI, upper respiratory tract infection; us-qPCR, ultrasensitive quantitative PCR.

We present the missingness testing for the measurement of hemoglobin as it was particularly affected with only 51% of the values collected. Missingness was nonsignificant between both HD versus LD (47% versus 40% respectively, p = 0.2) and ND versus LD (49% versus 40% respectively, p = 0.1).

Ethical considerations

Written informed caregiver consent was obtained at inclusion, and a sample donation form was filled out for sample storage and use for further evaluation of diagnostic methods.

Ethics approval was obtained from the Ifakara Health Institutional Review Board (IHI/IRB/EXT/16-2015), the Tanzanian National Institute for Medical Research (NIMR/HQ/R.8a/Vol.IX/1789), and the Swiss Ethikkommission Nordwest-und Zentralschweiz (EKNZ-UBE-15/03).

This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (S1 STROBE Checklist).

Results

Cohort selection and Pf parasitemia prevalence

Population

Of 3,192 recruited patients, 3,004 had sufficient sample volume for diagnostic analyses, and 203 were excluded because of discrepancies between onsite standard mRDT results and those performed later on frozen blood (Fig 1). These discrepancies were likely due to the suboptimal specificity of a single lot of standard mRDTs used onsite and were excluded to eliminate cohort contamination (i.e., those with a negative standard mRDT should not be exposed to antimalarials). The performance issues on this lot of standard mRDTs was independently reported by the local health authorities and verified by HRP2 antigen concentration in an associated study [14]. Of the 203 faulty tests, 84% (n = 170/203) had false positive onsite standard mRDT results (i.e. receiving antimalarials despite having ND Pf parasitemia) and 16% (n = 33/203) had false negative results (i.e. not receiving antimalarials despite having HD malaria). Fortunately, all the children in the latter category, who were put at risk of untreated HD malaria by the faulty tests spontaneously cleared the infection without treatment by day 7. The e-POCT (electronic point-of-care test) clinical decision support tool reacted to severity signs in this group of false negative children, referring 15% of them (n = 5/33) directly to hospital or for a next day re-consultation, significantly more than were referred in the malaria-free false positive group (3%, n = 5/170, p = 0.003).

Fig 1 — After patient recruitment had ended, frozen blood from all 2,801 patients was tested for Pf by ultrasensitive qPCR, standard mRDT, and ultrasensitive mRDT. As the latter did not improve sensitivity beyond standard mRDT, it is hereafter excluded. ALMANACH, ALgorithms for the MANagement of Acute CHildhood illnesses; e-POCT, electronic point of care test; mRDT, malaria rapid diagnostic test; Pf, *Plasmodium falciparum*, qPCR, quantitative polymerase chain reaction; sd-mRDT,.

The proportion of participants receiving antibiotics was 20.7% (n = 523/2,527), 15.8% (n = 12/76), and 23.7% (n = 47/198) in children with ND, LD, and HD infections, respectively. No significant differences in antibiotic prescription were observed between ND versus LD groups (RR = 0.7, 95% CI 0.4–1.3, p = 0.3) or HD versus LD groups (RR = 0.7, 95% CI 0.4–1.1, p = 0.2) and could thus not explain the differences described hereafter.

Pf parasitemia prevalence

Detailed performance measures of the 3 tests of interest (standard mRDT, ultrasensitive mRDT, and ultrasensitive qPCR) were previously described [14]. Pf positivity was 7.1% (n = 199/2,801) by standard mRDT, 7.5% (n = 209/2,801) by ultrasensitive mRDT, and 9.8% (n = 274/2,801) by ultrasensitive qPCR. Standard mRDT and ultrasensitive qPCR results are presented in Table 2; ultrasensitive mRDT results can be found in the supplement, S1 Table. The rate of “false positives” compared with ultrasensitive qPCR was 0.04% (n = 1/2801) by standard mRDT and 0.3% (n = 8/2801) by ultrasensitive mRDT. A total of 27.7% (n = 76/274) and 26.6% (n = 73/274) of ultrasensitive qPCR+ Pf infections were not detected by standard mRDT and ultrasensitive mRDT, respectively. Thus, the number of children with HD, LD, and ND was 198, 76, and 2,527, respectively.

Table 2. Results of standard mRDT and ultrasensitive qPCR tests.

		us-qPCR (gold standard)
		−	+	Total
sd-mRDT	−	2,526	76 LD: us-qPCR-positive cases missed by sd-mRDT	2,602
sd-mRDT	+	1	198 HD: sd-mRDT-positive cases confirmed by us-qPCR	199
		2,527 ND: Total us-qPCR-negative samples	274	2,801

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HD, high-density Pf infection; LD, low-density Pf infection; ND, no detectable Pf parasitemia; sd-mRDT, standard malaria rapid diagnostic test; us-qPCR, ultrasensitive quantitative PCR.

Distribution of Pf parasitemia in febrile children

Demographic distribution

LD infections disproportionally affected younger children, in whom the predicted probability of having LD infection was higher than that of HD infection until 30 months of age (Fig 2). Patients with LD infections were on average 10.6 months younger than those with HD infections (95% CI 7.0–14.3 months, p < 0.001, median 13.1 versus 25.6 months), whereas no significant age difference was observed between LD and ND groups (95% CI 2.6–2.9 months, p < 0.9) (Tables 3 and 4). This correlation could also be seen at the parasite density level (Fig 3). No differences between male and females were observed among any groups (Tables 3 and 4).

Fig 2 — **(A)** Predicted probability of being assigned to the HD or LD group according to age (fitted fractional polynomial plot). Shaded regions are 95% CI; **(B)** Predicted probability of parasite density by age (fitted fractional polynomial plot); **(C)** Number of patients with HD and LD parasitemia identified for each month of the 2016 recruitment period. HD, high-density Pf infection, LD, low-density Pf infection; RDT, rapid diagnostic test; ND, no detectable Pf parasitemia; sd-mRDT, standard malaria RDT; us-qPCR, ultrasensitive quantitative polymerase chain reaction.

Table 4. Comparative analysis of demographic and epidemiological features (LD versus HD).

	HD parasitemia sd-mRDT+/us-qPCR+		LD parasitemia sd-mRDT-/us-qPCR+		LD versus HD parasitemia
	Prevalence				Crude bivariate analysis				Adjusted (Age)
Total	%	Prevalence	%	Prevalence
n = 2,801	7.0	198/2,801	2.7	76/2,801
Demographics	Median	IQR	Median	IQR	RR_crude	95% CI	p-value
Age (months)	25.6	(15.3–37.4)	13.1	(8.4–21.0)	0.9	(0.9; 1.0)	<0.001	^a	→ Potential confounder
	%	Total = 198	%	Total = 76	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Sex (female)	48.0	95	50.0	38	1.1	(0.6–1.8)	0.8		1.2	(0.7–2.2)	0.5
Season (post rainy)	81.8	162	81.6	62	1.0	(0.6–1.5)	1.0		0.9	(0.5–1.5)	0.7
District (Kinondoni)	39.9	73/183	57.7	41/71	1.7	(1.1–2.3)	0.01	^a	1.7	(1.1–2.3)	0.02	^a
District (Temeke)	56.3	103/183	42.3	30/71	0.7	(0.4–1.0)	0.05	^a	0.7	(0.4–1.0)	0.06
District (Ilala)	3.8	7/183	0.0	0/71	–	–	–		–	–	–
Treatment exposure	%	Total = 198	%	Total = 76	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Antimalarials	100.0	198	0.0	0	–	–	–		–	–	–
Antibiotics	23.7	47	15.8	12	0.7	(0.4–1.1)	0.2		0.7	(0.4–1.1)	0.2

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Low-density (LD: sd-mRDT-/us-qPCR+) versus high-density Pf parasitemia (HD: sd-mRDT+/us-qPCR+).

^ap < 0.05 and considered as statistically significant.

Fig 3 — **(A)** Prevalence of severe illness amongst all patients (left) versus a subgroup excluding severely malnourished patients (right). **(B)** Log parasite densities in Pf-positive cases (qPCR-detectable: LD and HD), in the presence or absence of severe illness. **(C)** Prevalence of patients with moderate-to-severe anemia. **(D)** Log parasite densities in Pf-positive cases (qPCR-detectable: LD and HD), in the presence or absence of moderate-to-severe anemia. Severe malnutrition is defined as weight-for-age Z-score < −3 and/or MUAC <5–11 cm. Moderate-to-severe anemia is defined as memoglobin <9 g/dl. *p < 0.05. HD, high-density Pf infection, LD, low-density Pf infection; RDT, rapid diagnostic test; MUAC, mid-upper arm circumference; ND, no detectable Pf parasitemia; ns, nonsignificant; sd-mRDT, standard malaria RDT; us-qPCR, ultrasensitive quantitative polymerase chain reaction.

Seasonal distribution

LD infections mirrored the seasonal distribution pattern of HD infections (Fig 2) occurring mostly during the post-rainy season with a peak between June and September. Compared with ND, LD carriage was 4.2-fold more likely to occur during the malaria season (95% CI 2.4–7.2, p < 0.001, Table 3). LD carriage dropped to near zero outside the malaria season.

Age was identified as a potential confounder in comparisons between HD and LD groups, whereas season was identified as a potential confounder in comparisons between ND and LD groups (Tables 3–5).

Clinical presentation of children with Pf infections

LD versus ND

Overall, 43% (n = 33/76) of children with LD parasitemia were ascribed the diagnosis of undifferentiated fever (13% more than the ND group [29.8%, n = 753/2527], RR = 1.8, 95% CI 1.1–2.7, p = 0.01). In contrast, the LD group was less likely to have cough (RR = 0.5, 95% CI 0.3; 0.7, p = 0.001) and pneumonia (RR = 0.4, 95% CI 0.2; 0.8, p = 0.01) (Table 5) No differences amongst any groups were observed for gastrointestinal symptoms, skin problems, pharyngitis, or clinical danger signs. (Tables 5–6). No difference was found between LD and ND groups regarding anemia (RR = 1.0, 95% CI 0.6; 1.9, p = 0.8) (Fig 3) or levels of inflammatory markers (CRP and PCT levels) (Fig 4).

Table 6. Comparative analysis of clinical presentation, lab results and diagnoses at day zero.

LD versus HD (low versus high-density parasitemia).

	HD parasitemia sd-mRDT+/us-qPCR+		LD parasitemia sd-mRDT-/us-qPCR+		LD versus HD parasitemia
	PREVALENCE				CRUDE BIVARIATE ANALYSIS				ADJUSTED (Age)
Signs and Symptoms	%	Total = 198	%	Total = 76	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Danger signs present	2.0	4	1.3	1	0.7	(0.1–2.4)	0.7		0.4	(0.1–2.1)	0.4
Respiratory distress	0.5	1	1.3	1	1.8	(0.2–3.4)	0.5		1.3	(0.1–3.2)	0.8
Cough	44.4	88	39.5	30	0.9	(0.6–1.3)	0.5		0.7	(0.5–1.1)	0.2
Pharyngitis	1.0	2	1.3	1	1.2	(0.2–3.0)	0.8		1.0	(0.1–2.9)	1.0
Abdominal pain	12.6	25	6.6	5	0.6	(0.2–1.2)	0.2		1.1	(0.5–2.0)	0.9
Loss of appetite	2.5	5	3.9	3	1.6	(0.4–2.6)	0.5		1.3	(0.4–2.7)	0.6
Vomit	24.2	48	26.3	20	1.1	(0.7–1.6)	0.7		1.0	(0.6–1.5)	0.9
Diarrhea	8.1	16	14.5	11	1.5	(0.9–2.3)	0.12		1.3	(0.7–2.1)	0.4
Fever only	23.2	46	13.2	10	0.6	(0.3–1.0)	0.07	∼	0.6	(0.3–1.1)	0.09	∼
FWS^b	--	--	43.4	33	–	–	–		–	–	–
Lab results and measures	Mean	95% CI	Mean	95% CI	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Temperature (°C)	39.0	(38.8–39.1)	38.3	(38.1–38.5)	0.4	(0.3–0.5)	<0.001	^a	0.4	(0.3–0.6)	<0.001	^a
Preconsult fever duration	1.7	(1.5–1.8)	1.3	(1.1–1.5)	0.7	(0.6–1.0)	0.02	^a	0.7	(0.6–1.0)	0.06	∼
Hemoglobin (g/dL)	8.9	(8.5–9.2)	9.6	(9.2–10.1)	1.3	(1.0–1.6)	0.02	^a	1.6	(1.2–2.1)	0.00	^a
	Median	IQR	Median	IQR	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
CRP (mg/L)^e	10.0	(10.0-40.0)	0.0	(0.0-10.0)	1.0	(0.9–1.0)	0.02	^a	1.0	(0.9–1.0)	0.05	^a
PCT (ug/L)	5.5	(0.6-21.1)	0.3	(0.1-0.4)	0.7	(0.5–1.0)	0.04	^a	0.7	(0.5–1.0)	0.07	∼
Diagnoses	%	Total = 198	%	Total = 76	RR_crude	95% CI	p-value		RR_adj	95% CI	p-value
Anemia (moderate-to-severe)^c	74.0	77/104	56.5	26/46	0.6	(0.3–1.0)	0.04	^a	0.3	(0.1–0.7)	0.001	^a
Sickle cell disease (HbSS)^d	14.9	13/87	10.0	4/40	0.7	(0.3–1.5)	0.5		0.7	(0.3–1.6)	0.5
Sickle cell trait (HbAS)^d	0.0	0/87	0.0	0/40	0.7	(0.3–1.5)	0.5		0.7	(0.3–1.6)	0.5
Malnutrition	5.6	11	9.2	7	1.4	(0.7–2.3)	0.3		1.2	(0.6–2.1)	0.6
Severe malnutrition	1.5	3	5.3	4	2.1	(0.8–3.1)	0.1		1.6	(0.5–2.9)	0.3
Severe illness	11.6	23	11.8	9	1.0	(0.5–1.7)	1.0		1.1	(0.6–1.8)	0.8
URTI	5.6	11	13.3	10/75	1.8	(1.0–2.7)	0.04	^a	1.5	(0.8–2.4)	0.2
Pneumonia	23.7	47	13.2	10	0.6	(0.3–1.0)	0.06	∼	0.6	(0.3–1.1)	0.08	∼
HIV	0.5	1/185	1.5	1/68	1.9	(0.2–3.5)	0.5		1.7	(0.2–3.5)	0.6
Suspected viral infection	0.5	1	42.1	32	5.3	(4.4–5.5)	<0.001	^a	5.3	(4.4–5.5)	<0.001	^a
Suspected bacterial infection	0.5	1	1.3	1	1.8	(0.2–3.4)	0.5		2.5	(0.3–3.6)	0.3

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^ap < 0.05 and considered as statistically significant

^bFWS is diagnosed using sd-mRDT, and it is thus not present in HD infection.

^cModerate-to-severe anemia: Hb < 9 g/dL.

^dHbSS only investigated in samples with sufficient blood volume (i.e., 40/78 LD, 87/198 HD, and 895/2,527).

Fig 4 — Violin plots showing the distribution in the concentrations of **(A)** PCT and **(B)** CRP found among ND, LD, and HD groups. Thick black bands: median. Dotted lines: quartiles. CRP was measured using a categorical quantitation test. Four categories exist: <10 mg/L, 10–40 mg/L, 40–80 mg/L, and >80 mg/L. The lower limit of this range is represented in the plot. *p < 0.05. CRP, C-reactive protein; HD, high-density Pf infection; LD, low-density Pf infection; ND, undetectable Pf parasitemia; ns, nonsignificant; PCT, procalcitonin; Sd-mRDT, standard malaria rapid diagnostic test; us-qPCR, ultrasensitive quantitative PCR.

LD infections were 3-fold more likely to occur in severely malnourished children when compared with ND (95% CI 1.1–7.5, p = 0.03, Table 5), a difference not found between HD and LD groups (RR = 1.6, 95% CI 0.5–2.9, p = 0.3, Table 6). This explains the higher prevalence of “severe illnesses” in LD compared with ND (RR = 2.2, 95% CI 1.1–4.0, p = 0.02), an observation which became statistically insignificant when controlling for severe malnutrition (RR = 1.8, 95% CI 0.8–4.0, p = 0.2) (Fig 3A, Table 5). Indeed, among ultrasensitive qPCR+ patients, no trend between parasite density and illness severity was observed, and mean parasitemia was not different between those with severe and nonsevere illnesses (Fig 3B).

LD versus HD

Only markers of anemia and inflammation were significantly elevated in HD infections, Table 6). For instance, HD infections had significantly higher axillary temperatures compared with LD, (39.0°C versus 38.3°C, RR = 2.5, 95% CI 2.0–3.3, p < 0.001), whereas no differences were observed between LD and ND groups (Table 5). Additionally, moderate-to-severe anemia (<9 g/dl) was 3-fold more frequent in the HD group (RR = 3.3, 95% CI 1.4–10.0, p < 0.001) (Fig 3C) and corresponded to a mean difference of 0.7 g/dl hemoglobin (LD: 9.6 versus HD: 8.9 g/dl, 95% CI 0.2–1.4) (Table 6). This trend was also visible at the parasitemia level, in which children with moderate-to-severe anemia (<9 g/dl) had significantly higher parasite loads (5.1 × 10⁵ more parasites, 95% CI 5.4 × 10⁴ to 9.6 × 10⁵, p = 0.03) (Fig 3D). No differences were seen in sickle trait carriage or disease across any group (Table 6). Amongst inflammatory markers, children with HD infection had 17 ug/L higher mean procalcitonin (medians 0.3 ug/L versus 5.5 ug/L, RR = 1.4, 95% CI 1.0–2.0, p = 0.04) (Fig 4A) and 13.2 mg/L higher mean CRP (medians of a range of 0–10 mg/L versus 10–40 mg/L, p = 0.02) (Fig 4B).

Clinical outcome of children with Pf parasitemia

Clinical outcomes (LD versus ND)

Despite the fact that children with LD were not treated with antimalarials, neither the proportion of clinical failures (RR = 0.7, 95% CI 0.2–2.6, p = 0.5) (Fig 5A) nor the proportion of secondary hospitalizations (RR = 0.9, 95% CI 0.2–3.5, p = 0.9) (Fig 5B) were significantly different between LD and ND groups (Table 7). The frequency of deaths was zero in LD children and or near zero (0.3%, n = 8/2,527) in ND children (Table 7). No significant differences were observed in secondary outcomes, such as the number of days until fever clearance (postconsultation) and the duration of secondary hospital admissions. Finally, none of the 76 children with LD infections tested positive for HD Pf parasitemia in the first 7-day follow-up period despite not receiving antimalarials.

Table 7. Comparative analysis of health outcomes.

	ND sd-mRDT-/us-qPCR-		LD parasitemia sd-mRDT-/us-qPCR+		LD versus ND parasitemia
	Prevalence				Crude bivariate analysis			Adjusted (season)
Outcomes	Mean	95% CI	Mean	95% CI	RR_crude	95% CI	p-value	RRadj	95% CI	p-value
Days to fever clearance	3.5	(3.4–3.5)	3.2	(2.8–3.5)	0.9	(0.8 to −1.0)	0.2	0.9	(0.8–1.1)	0.4
Admission duration (days)	5.1	(4.1–6.0)	3.0	(−22.4 to 28.4)	0.8	(0.4–1.6)	0.5	0.7	(0.3–1.5)	0.4
	%	Total = 2,527	%	Total = 76		95% CI	p-value	RRadj	CI95%	p-value
Clinical failure	4.0	101	2.6	2	0.7	(0.2–2.6)	0.6	0.9	(0.2–3.5)	0.9
Secondary hospitalization	2.8	72	2.6	2	0.9	(0.2–3.5)	0.9	1.0	(0.2–4.1)	0.9
Death	0.3	8	0.0	0	–	–	–	–	–	–

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LD versus ND (low-density versus undetectable Pf parasitemia).

See S2 Table for the definition of clinical failure.

HD, high-density Pf infection; LD, low-density Pf infection; RR, risk ratio; RR_adj, adjusted RR. sd-mRDT, standard malaria RDT; us-qPCR, quantitative PCR.

Clinical outcomes (LD versus HD)

In contrast, children with HD infections were 3.3-fold more likely to be admitted to hospital during the 28 days of follow-up (95% CI 0.1–1.0, p = 0.06) when compared to LD (Fig 5B). No differences were observed in the duration of secondary hospital admissions nor in the time to fever clearance (Table 8).

Table 8. Comparative analysis of health outcomes.

	HD parasitemia sd-mRDT+/us-qPCR+		LD parasitemia sd-mRDT-/us-qPCR+		LD versus HD parasitemia
	Prevalence				Crude bivariate analysis				Adjusted (age)
Outcomes	Mean	95% CI	Mean	95% CI	RR_Crude	95% CI	p-value		RR_adj	95% CI	p-value
Days to fever clearance	3.5	(3.2–3.7)	3.2	(2.8–3.5)	0.9	(0.7–1.0)	0.1		0.9	(0.7–1.0)	0.1
Admission duration (days)	3.6	(3.0–4.2)	3.0	(−22.4 to 28.4)	0.7	(0.2–2.3)	0.5		0.5	(0.1–2.1)	0.4
	%	Total = 198	%	Total = 76		95% CI	p-value		RR_adj	95% CI	p-value
Clinical failure	3.0	6	2.6	2	0.9	(0.2–4.4)	0.9		0.9	(0.2–4.9)	0.9
Secondary hospitalization	10.1	20	2.6	2	0.3	(0.1–1.0)	0.1	∼	0.3	(0.1–1.0)	0.06	∼
Death	0.0	0	0.0	0	–	–	–		–	–	–

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LD versus HD (low-density versus high-density Pf parasitemia).

See S2 Table for the definition of clinical failure.

HD, high-density Pf infection; LD, low-density Pf infection; RR, risk ratio; RR_adj, adjusted RR. sd-mRDT, standard malaria RDT; us-qPCR, quantitative PCR.

Discussion

This study explores the clinical consequences of using highly sensitive diagnostic tools (ultrasensitive qPCR and ultrasensitive mRDT) for the detection of LD Pf parasitemia amongst febrile pediatric outpatients in a moderate endemicity setting. In this cohort of 2,801 Tanzanian children, the prevalence of Pf parasitemia was 9.8% by ultrasensitive qPCR. A quarter of these infections were not detected by both standard mRDTs and ultrasensitive mRDTs. The performance of the ultrasensitive-mRDT was previously tested on this cohort, in which it was also described as having near identical sensitivity and specificity to standard mRDTs [14]. The children with LD infections did not have a significantly different clinical outcome compared with Pf-negative children, despite not having received antimalarial treatment.

It was previously thought that LD infections and asymptomatic carriage mostly occurred in high-endemicity areas because of a higher immune tolerance and control. However, it is becoming clear that these infections are even more common in regions with low malaria endemicity after a recent period of high transmission [17]. This trend raises the question of whether LD infections have evolved as a survival strategy to maintain parasite transmission [18]. Indeed, these persistent, slowly oscillating low parasite densities may persist in untreated individuals for several months to years [19]. Interestingly, in our study, LD infection prevalence fell to zero during the non-malaria season despite continued testing, perhaps an indication that LD infection was not functioning as an off-season reservoir. Larger epidemiological surveys are required before such conclusions can be made. In this context, LD carriage may rather represent passing self-resolving Pf infections, which are more or less rapidly cleared by children according to their level of immunity (children with severe malnutrition had indeed a much higher rate of LD infections).

The mechanism behind the long-term asymptomatic maintenance of LD infections is thought to rely on immunological tolerance, in which the presence of neutralizing antibodies is postulated to keep parasitemia at low levels [18]. This could also explain the age trend observed in our study, in which parasitemia followed a directly proportional association with age, and the peak probability of LD infections occurred in infants under 9 months old who are under the protection of maternal passive immunity. In malaria-endemic countries, this age group has a significantly lower risk of developing severe malaria [20, 21]. This natural resistance in infants is likely to rather rely on passive immunity maternal antibodies, which impair the cytoadherence of parasitized red blood cells [22]. Further study into the immunological mechanism of LD carriage is needed before conclusions can be drawn on the origin of infant resistance to severe malaria.

As expected, the presence and severity of anemia had a directly proportional relationship with parasitemia amongst ultrasensitive qPCR+ individuals. However, although moderate-to-severe anemia (<9 g/dl) was significantly more frequent in HD compared with either LD or ND, no differences in hemoglobin levels were found between LD and ND groups. Sickle cell anemia is known to be protective of HD Pf parasitemia, and previous studies have revealed that these patients are also predisposed to LD carriage [23]. In this study, however, no differences in sickle cell disease or trait were found among any groups, albeit that the analyses were limited by the low prevalence of the HbSS trait. Thus, no associations between anemia and LD carriage were found within the follow-up timeframe of this cohort.

As exposure to Pf antigens is essential to transform passive maternal immunity into an active memory response, an argument can be made that asymptomatic LD carriage in children may be beneficial in the long term [24, 25]. Indeed, it has been previously shown that frequent superinfections (i.e., a high number of concurrent clones) can be protective against clinical malaria [26]. A counterargument is that the long-term stress of the infection may be associated with increased chronic morbidity and all-cause mortality [27]. However, these events are not measurable at the outpatient level or in the timeframe of acute febrile disease. Following this, our study found no statistically significant clinical impact of untreated LD parasitemia when compared with febrile controls without detectable Pf parasitemia (ND). In contrast, untreated patients with LD infections fared significantly better than those with HD infections (who were treated with antimalarials). For instance, despite treatment, HD infections had a significantly increased risk of developing severe outcomes, necessitating secondary hospitalization over the 28-day follow-up period. Critically, no differences were seen in the number of clinical failures at day 7 when the LD group was compared with either HD or ND, despite the fact that LD patients did not receive antimalarial therapy. This indicates that these LD infections represented either self-resolving fevers or an incidental finding in children with an alternative (most often viral) infection. However, as the pyrogenic threshold of parasitemia has been previously described to fall well within standard mRDT limits of detection, it is unlikely that LD infection was the primary cause of the febrile episode and the possibility of synergistic pyrogenic interactions with coinfecting viruses could also be possible [28]. Indeed, children with LD infections were significantly more likely to have suspected viral infections compared with either HD or ND groups according to their clinical presentation (undifferentiated fever), low level CRP and PCT (which are commonly associated with bacterial infections when high) and good outcome without antibiotic treatment. The bacteremia and sepsis in this study almost exclusively occurred in Pf-negative children (93%; n = 14/15).

Another question raised by these findings is whether LD infections are actually just clinically precocious HD infections. However, none of the children with LD infections had persistent fever that later tested positive for HD Pf parasitemia during the first 7 days of follow-up, despite not receiving antimalarials. Importantly, the data of this study were collected using electronic clinical decision support algorithms, which guided clinicians to appropriate management strategies and diagnoses. This situation differs significantly from routine care, in which clinicians are much more likely to diagnose and treat malaria regardless of test results. In this situation, the use of overly sensitive malaria diagnostic tests would likely result in even more overprescriptions and, possibly, missed alternate diagnoses. However, the clinical impact of these potentially missed diagnoses would be limited as the vast majority of these LD children were suffering from presumed viral infections, which resolved by themselves without antibiotic treatment.

Limitations and further research

As this cohort only included children between 2 and 59 months of age, it is not generalizable to adults or neonates who have different immunological characteristics. Further, as all the patients were febrile, the association to fever itself cannot be drawn. More research is required in more geographically and clinically diverse environments (including community-based studies and healthy controls) that will provide the statistical capacity to assess the aparasitemic cut-offs for Pf parasite-attributable morbidity. Longer-term follow-up models will also help investigate the potential importance of parasite carriage and recurrent infections. Finally, this study does not investigate causality of LD parasitemia, and thus cannot answer what immunologic, environmental, or genetic factors (of the host, parasite, or vector) may cause a person to resist infections progressing to higher parasitemia. The multifactorial possibilities merit multiple in depth studies. Of particular interest may be an investigation into the effect of coinfections, which may have an immunomodulatory influence on the control Pf coinfections, such as has been suggested for the gut microbiome [29]. For example, there is specific evidence that viral infections such as influenza and measles may reduce parasite density in febrile children, and this poses an potentially important research question during the outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [30].

Impact and recommendations

Currently, WHO uses 2 case definitions for malaria depending on the level of transmission: In areas with moderate-to-high transmission where “malaria-control” is the aim, cases are defined as any symptomatic person with (any) positive diagnostic test. However, no symptoms are necessary to define malaria in “malaria elimination” settings [31]. In a clinical context, not having a parasitemic cut-off for the definition of malaria may cause significant confusion. As clinically inconsequential carriage may occur alongside other serious diseases, the use of ultrasensitive diagnostics to detect LD Pf parasitemia may create red herring signals that mislead the clinician to overlook the true underlying diagnosis if not well trained. Thus, even though our study did not show a risk of missing a serious infection, diagnostic sensitivity of parasite detection must still be adapted to clinical relevance (i.e., there is a need to define parasitemic thresholds to guide clinicians on whether the detected parasites are likely to be symptomatic and/or a risk for community transmission). More importantly, training and guidance to clinicians should be provided to help manage febrile patients in an integrated way, through the provision of (electronic) evidence-based algorithms and guidelines [32]. Indeed, in this study, clinicians strictly followed electronic algorithms, which are not yet widely available elsewhere and may have helped avoid missing serious infections.

Thus, it is important to appreciate that the need for administering antimalarial therapy is proportional to parasite density. LD Pf parasitemia infections must be targeted to achieve elimination [33], but our study shows that there is no short-term consequence to withholding antimalarials from acutely febrile individuals with LD infection in the context and timeframe of an outpatient setting. These results bolster several robust studies, which conclude that it is safe to use only standard mRDTs in malarial diagnosis as is recommended in the current WHO guidelines [10–12, 34].

Conclusion

In this study in a moderate malaria endemicity setting, LD Pf parasitemia infections undetected by mRDT did not present acute health concerns in children in an outpatient setting. These LD infections may thus either represent benign self-resolving fevers or an incidental finding in children with other infections, likely of viral origin and thus requiring no antibiotic treatment. Our findings suggest that implementing ultrasensitive malaria diagnostics to detect LD infections is neither useful nor deleterious (except for wasting resources) in this context.

Supporting information

S1 STROBE checklist. STROBE, Strengthening the Reporting of Observational Studies in Epidemiology.

(DOCX)

Click here for additional data file.^{(33.8KB, docx)}

S1 Table. Results of standard mRDT and ultrasensitive mRDT stratified by ultrasensitive qPCR.

HD, high-density Pf infection; LD, low-density Pf infection; ND, no detectable Pf parasitemia; sd-mRDT, standard malaria RDT; us-mRDT, ultrasensitive-mRDT (Alere); us-qPCR, ultrasensitive quantitative PCR.

(DOCX)

Click here for additional data file.^{(14.5KB, docx)}

S2 Table. Definition of clinical failure (primary outcome measure).

Adapted from Keitel et al. [13].

(DOCX)

Click here for additional data file.^{(18.3KB, docx)}

Acknowledgments

We thank the patients and caretakers involved in this study for their contribution to work toward improving the diagnosis of fever in children.

Abbreviations

ALMANACH: ALgorithms for the MANagement of Acute CHildhood illnesses
CRP: C-reactive protein
e-POCT: electronic point of care test
HD: high-density
HRP-2: Pf Histidine-Rich Protein-2
ICMI: Integrated Management for Childhood Illnesses
LD: low-density
mRDT: malaria rapid diagnostic test
MUAC: mid-upper arm circumference
ND: no detectable
PCT: procalcitonin
Pf: Plasmodium falciparum
qPCR: quantitative polymerase chain reaction
RR: risk ratio

Data Availability

The data set and data dictionary are available from https://github.com/epfl-iglobalhealth/Hartley2020-PLoSMedicine.

Funding Statement

Analyses were funded by a Bill & Melinda Gates Foundation grant awarded to VDA https://www.gatesfoundation.org/ (grant number: OPP1163434). Laboratory work was supported by the Swiss National Science Foundation http://www.snf.ch/en/Pages/default.aspx (grant numbers 310030_159580 and IZRJZ3_164182). Malaria RDTs were contributed free of charge by Alere/Standard Diagnostics (now Abbott) https://www.alere.com/en/home/products-services/brands/sd-bioline.html The funders and donors had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS Med. doi: 10.1371/journal.pmed.1003318.r001

Decision Letter 0

Clare Stone

17 Feb 2020

Dear Dr Hartley,

Thank you for submitting your manuscript entitled "Clinical relevance of low-density Plasmodium falciparum parasitaemia in untreated febrile children: a retrospective cohort analysis" for consideration by PLOS Medicine.

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PLoS Med. doi: 10.1371/journal.pmed.1003318.r002

Decision Letter 1

Emma Veitch

26 May 2020

Dear Dr. Hartley,

Thank you very much for submitting your manuscript "Clinical relevance of low-density Plasmodium falciparum parasitaemia in untreated febrile children: a retrospective cohort analysis." (PMEDICINE-D-20-00426R1) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

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In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

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Requests from the editors:

*Currently the title has been phrased per the usual PLOS Medicine style, which is good (study question followed by the type of study design after a colon) but one reviewer questions whether it was really a retrospective analysis - the authors could consider this point and rephrase as needed.

*In the abstract conclusions, it would be good to take on board the reviewers' points (particularly reviewer 1) that the main finding of the analysis (failure to see a difference in clinical outcomes between LD and ND children) may have been presented too strongly, ie as a negative effect rather than failure to see an effect. This distinction could be made more clearly.

*In the last sentence of the Abstract Methods and Findings section, please describe briefly any key limitation(s) of the study's methodology.

*At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

*In Materials and Methods, Design/Patient population and context section, this describes the work as a retrospective analysis of a prospective cohort study. However later on it's presented as an analysis based on patients enrolled in a randomized trial. I think this distinction (whether it was a cohort or a RCT) is likely to be confusing to readers, it may be clearer to say that this is an analysis using data from a RCT but combining data from the trial arms and therefore treating it like a cohort? Assume that this is indeed what was done?

*We'd suggest also clarifying if the analysis presented here was prospectively planned out in a protocol or analysis plan? Please state this (either way) early in the Methods section.

a) If a prospective analysis plan (from your funding proposal, IRB or other ethics committee submission, study protocol, or other planning document written before analyzing the data) was used in designing the study, please include the relevant prospectively written document with your revised manuscript as a Supporting Information file to be published alongside your study, and cite it in the Methods section. A legend for this file should be included at the end of your manuscript.

b) If no such document exists, please make sure that the Methods section transparently describes when analyses were planned, and when/why any data-driven changes to analyses took place.

c) In either case, changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

*As noted by one reviewer, there are a few slightly ungrammatical phrases in the paper, I've suggested a few examples below. It may be worth cross-reading the paper before resubmitting to try to tidy some of these up.

*Abstract - "The App collected at the same time systematic clinical data (symptoms, signs and laboratory tests on day 0 and at follow-up visits" - perhaps "The app SIMULTANEOUSLY collected clinical data ..."

*Abstract - "are used to propose (and record) a diagnosis and management plan" - in the paper "propose" is used in a number of places where in English, "suggest" or "put forward" might read more naturally.

*Abstract - "Concerning malaria, only sd-mRDT+ cases received antimalarials" - "Only sd-mRDT+ cases received antimalarials.."

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Comments from the reviewers:

Reviewer #1: See attachment

Michael Dewey

-----------------------------------------------------------

Reviewer #2: This is a well performed and well analysed study and a well written article. It adresses a clinically quite important subject/research question, namely the potential benefit vs even negative impact of using the recently developed ultrasensitive mRDTs vs the standard mRDTs - the article provides a rather credible, clear and important answer to this primary research question

The article also discusses a few general issues related to parasite densities of Pf infections such as maternal antibodies, sickle cell trait and concomitant infections - which I find adds to my interest in the article

Minor comments

a) I believe in Title of Table 1 = "sub-cohort" should be ""sub-cohorts"

b) maybe add one ref in rel to the text on withholding malaria treatment to mRDT neg febrile children in malaria endemic countries = Msellem et al PLoS Med 6:e 1000070 , 2009

c)definitely consider adding one ref on the effect of viral infections reducing malaria parasite densities in febrile Children = Rooth and Björkman Am J Trop Med 47: 675 , 1992 - this supports the findings in the present article

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Reviewer #3: This manuscript indicates that failure to treat febrile P. falciparum infection with antimalarial drugs in Tanzanian children under 5 years with infections detectable by ultrasensitive PCR but not by standard RDT has no negative health consequences. The authors conclude that ultrasensitive diagnostics for Pf infection offer no clinical benefit in an urban primary care setting where malaria endemicity is low. (Dar es Salaam in this case.)

Major comments

1) Strengths of the manuscript include: a) utilization of an electronic algorithm for clinical decision making that includes syndromic features and point of care diagnostics that are affordable in resource constrained settings, i.e., Keitel et al PLoS Med 2017; b) Comparison of Pf infections detected by ultrasensitive PCR to those detected by ultrasensitive RDT; c) The 28 day follow up period lends credibility to the claim that lack of administration of antimalarials in children who are positive for Pf by ultrasensitive PCR but negative by standard RDT (for PfHRP2) is appropriate; d) The study is clearly ethical as studies involving diagnosis by ultrasensitive PCR were done retrospectively.

2) Terminology in the manuscript with respect to "high density", "low density" parasiteimia, etc. is confusing and potentially misleading to some readers. This is particularly true in settings in sub-Saharan Africa where the Pf biomass is readily detectable by microscopic inspection of blood smears and RDTs are not routinely performed in order to reduce cost.

3) Severe malnutrition is a major confounder in the analysis. More detail on the criteria for the diagnosis of "severe malnutrition" in the ePOCT algorithm is needed.

4) Statements with respect to "severe illness" and anaemia as "moderate to severe" (as in Table 4A and 4B) are confusing and differ from those in the PLoS Med 2017 paper. Hb concentration values in the manuscript are given as mmol/L whereas values in the 2017 paper are presented as g/L. Secondly, the PLoS Med paper (Fig. 2) defines severe anemia as Hb <60 g/L (Hb 6 g/dL or 3.72 mmol/L). The high density parasitemia patients in this manuscript had a median value of 8.9 mmol/L (14.3 g/dL) and referred to as "severe anaemia". Please clarify what is meant by severe anaemia and what cut off values are used in this urban population. Attention to this detail is particularly important to the Discussion (e.g., lines 381-389).

Minor comments

1) Line 11. Capital letters are omitted from the institutional unit.

2) Acronyms are over used. RDT and PCR are generally understood terms but readability would be greatly improved by avoiding terms such LD, ND, us-qPCR+ vs. qPCR- etc.

3) Table 1 is unnecessary and could be omitted.

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Reviewer #4:

The paper is written in a rather unconventional way. Nothing wrong with innovation but I have to admit I found it hard to find my way around this paper. More confusion comes from near complete similarity of standard RDT+ and us-RDT+ study participants. Since the difference in sensitivity between the two RDTs is minimal, despite the name "ultrasensitive" there is very little gained from testing with us-RDTs. The us-RDTs missed the majority of the low density infections detected by PCR. Hence the inclusion of a patient group "us-RDT+" adds no information but adds considerable confusion. Would the authors consider omitting the data on us-RDTs since it contributes nothing meaningful to description of clinical sequelae of low density infections? I understand the desire to publish the data but the inclusion of the usRDT data do not make the paper stronger.

Abstract

Provide total numbers included in each of the two groups: sd-mRDT-/us-qPCR+, sd-mRDT-/us-qPCR-, sd-mRDT+/us-qPCR+.

"Pf positivity rate was 7.1% and 9.8% by sd-mRDT and us-qPCR respectively." What % of usRDTs were positive?

Intro

"A new easy-to-use and affordable ultra-sensitive mRDT (us-mRDT) was developed (Alere™, Abbott Diagnostics) able to detect the Pf Histidine-Rich Protein-2 (HRP-2) with ten-fold greater sensitivity to that of sd-mRDTs." I do not understand why the authors use reference #8 if their own group has made much more realistic estimates of the added sensitivity of us-RDT? "us-RDT identified few additional P. falciparum-positive patients as compared to co-RDT (276 vs 265 parasite-positive patients detected), with only a marginally greater sensitivity (75% vs 73%), using us-qPCR as the gold standard …" ( Hofman et al JID 2019).

"As many of the LD infections are also asymptomatic, these highly sensitive tests resurrect Koch's postulates of what defines a "pathogen", and at what concentration should a detected parasite be considered "disease-causing", necessitating the implementation of preventive or therapeutic interventions."

1) resurrect Koch's postulates - if they have not died they do not need resurrection.

2) parasitaemia is hardly physiologic - if possible the patient with parasitaemia should be treated - even if interventions do not benefit the patient directly, the patient should be treated to prevent transmission?

"It thus becomes important to assess at which point this gain in sensitivity surpasses its clinical benefit, …" Ultrasensitive diagnostics have not been developed for clinical management of patients. Please clarify this point.

The authors write at the end of the intro: "Thus these analyses aim to fill the gaps highlighted by the WHO technical committee for policy recommendations on highly sensitive point-of-care Pf malaria diagnostics by elucidating the prevalence and clinical presentation of LD parasitaemia detectable only by ultra-sensitive tools such as us-qPCR and us-mRDT and measuring its impact on clinical outcomes in febrile outpatients." Would it be possible to state clearly what the research question was?

Results:

Figure 1: please clearly indicate in the chart how many study participants were tested with 1) standard RDT, 2) us-RDT, 3) us-PCR?

Please add a table describing the demographic characteristics of 3 patient groups: low density, high density and no infections. In the table please indicate the numbers testing positive with which test (sd-RDT, us-RDT, usPCR.

If the authors insist to include the us-RDT data in the paper Table 2 is inappropriate and should be replaced with table S2.

How was "severe illness defined"?

Discussion

"LD infection prevalence fell to zero during the non-malaria season, perhaps an indication that LD infection was not functioning as an off-season reservoir, …" considering the limited sample size of the surveys the conclusions may be premature. It would take much more complete surveys of the entire population to justify the conclusion that low density infections do not contribute to transmission.

"Lower endemicity settings also have a lower diversity of parasites to which inhabitants may be more readily immune, and thus also partly explain the higher LD prevalence in recent low-endemicity settings." Shouldn't immunity clear infections and reduce the parasite prevalence?

"This study shows that, at least in a moderate malaria endemicity setting, low-density (LD) Pf parasitaemia infections undetected by mRDT did not present acute health concerns in children in an outpatient setting." Please consider rephrasing? The way the sentence currently reads the reader could think that prior to this study low density infections required acute health care. This is misleading. It would be correct to state that the study confirmed that low density infections do not require acute interventions but when detected should be treated if only to prevent transmission.

-----------------------------------------------------------

Any attachments provided with reviews can be seen via the following link:

[LINK]

Attachment

Submitted filename: hartley.pdf

Click here for additional data file.^{(57KB, pdf)}

PLoS Med. 2020 Sep 21;17(9):e1003318. doi: 10.1371/journal.pmed.1003318.r003

Author response to Decision Letter 1

10 Jun 2020

Attachment

Submitted filename: UltrasensitiveMalariaDiagnostics(Hartley_09June20)_Reviewer.pdf

Click here for additional data file.^{(822KB, pdf)}

PLoS Med. doi: 10.1371/journal.pmed.1003318.r004

Decision Letter 2

Thomas J McBride

14 Jul 2020

Dear Dr. Hartley,

Thank you very much for re-submitting your manuscript "Clinical relevance of low-density Plasmodium falciparum parasitaemia in untreated febrile children: a prospective cohort analysis." (PMEDICINE-D-20-00426R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by three of the original reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

Our publications team (plosmedicine@plos.org) will be in touch shortly about the production requirements for your paper, and the link and deadline for resubmission. DO NOT RESUBMIT BEFORE YOU'VE RECEIVED THE PRODUCTION REQUIREMENTS.

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

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We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Jul 21 2020 11:59PM.

Sincerely,

Thomas McBride, PhD

Senior Editor

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

Comments from the Academic Editor:

Minor points:

167 … “The arm of the trial did not affect any outcomes investigated.” Confusing, please rephrase

281 “All the children in the latter category, who were 282 put at risk of untreated HD malaria by the faulty tests were cured by day 7.” Better "spontaneously cleared the infection without treatment."

287 “As clinicians were guided by the decision support algorithms, the proportion of participants receiving antibiotics was more appropriate than what is generally observed in LMICs: This does not belong in the result section – this is part of the discussion.

“Interestingly, in our study, LD infection prevalence fell to zero during the non-malaria season, perhaps an indication that LD infection was not functioning as an off-season reservoir, albeit that larger epidemiological surveys are required before such conclusions can be made.” Indeed, this conclusion cannot be made and should not be stated in this form. Please indicate on how many samples this hypothesis is based on? How many patients were tested during the non-malaria season?

“Lower endemicity settings also have a lower diversity of parasites to which inhabitants may be more readily immune, and thus also partly explain the higher LD prevalence in recent low-endemicity settings.” Please explain what you mean by lower? Lower compared to what? do you refer to the ratio LD total number infections or the absolute prevalence. Please support this statement by appropriate references?

Since no data on HbF or HbSS are reported the discussion could be shortened by omitting the speculation related HbF and HbSS?

“diagnostic sensitivity must still be adapted to clinical relevance.” Can you please elaborate how this can be done – adapt the diagnostic sensitivity?

Requests from the editors:

1- Please ensure that the study is reported according to the STROBE guideline, and include the completed STROBE checklist as Supporting Information. 1 Please add the following statement, or similar, to the Methods: "This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (SChecklist)."

The STROBE guideline can be found here: http://www.equator-network.org/reporting-guidelines/strobe/

When completing the checklist, please use section and paragraph numbers, rather than page numbers.

2- Thank you for agreeing to make your data available. At this time, please update your data availability statement to provide the URLs/accession numbers/DOIs for data access.

3- Did your study have a prospective protocol or analysis plan? Please state this (either way) early in the Methods section.

b) If no such document exists, please make sure that the Methods section transparently describes when analyses were planned, and when/why any data-driven changes to analyses took place.

c) In either case, changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

4- Thank you for editing your title. However, please update further to: “Clinical relevance of low-density Plasmodium falciparum parasitaemia in untreated febrile children: a cohort study”

5- In the Abstract Methods and Findings, please include how the participants were recruited, the years during which the study took place, and some brief demographic information (eg, average age (SD), and sex breakdown).

6- Lines 40-43 of the Abstract could be condensed to say something to the effect of: “Treatment decisions were guided by a clinical decision support algorithm run on a mobile app, which also collected clinical data.

7- In the Abstract and Figure 1, please state how many patients were tested with standard RDT, us-RDT, and us-PCR.

8- In the Abstract and throughout, please present numerators and denominators alongside percentages.

9- Please delete the “Limitations” section header, and append the sentence on limitations to the end of the Abstract Methods and Findings section.

10- The second sentence of the Abstract Conclusion section should be worded a bit more cautiously: “These findings suggest LD parasitaemia...other infections, including those of viral origin.”

11- In the last sentence of the Abstract Conclusions, please rephrase to read: “These findings do not support a clinical benefit, nor additional risk (due to missed bacterial infections) to using ultra-sensitive malaria diagnostics at a primary care level.”

12- Thank you for adding an Author Summary. Please reformat to follow our guidelines:

https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

We ask authors to provide 2-3 single sentence bullet points for each of the following questions. Bullet points should be objective, brief, succinct, specific, accurate, and avoid technical language.

Why Was This Study Done? Authors should reflect on what was known about the topic before the research was published and why the research was needed.

What Did the Researchers Do and Find? Authors should briefly describe the study design that was used and the study’s major findings. Do include the headline numbers from the study, such as the sample size and key findings.

What Do These Findings Mean? Authors should reflect on the new knowledge generated by the research and the implications for practice, research, policy, or public health. Authors should also consider how the interpretation of the study’s findings may be affected by the study limitations.

13- In addition, please edit the last sentence of the Author Summary (currently line 88), to present your conclusions with more caution (e.g., "Our findings suggest a lack of risk or benefit in terms of clinical outcome ...").

14- Please remove trademark symbols throughout the manuscript.

15- Given that the ultra-sensitive mRDT has near identical sensitivity to standard mRDT in this cohort, the name is a bit confusing. Please mention this briefly early on (e.g., in the Introduction), and consider using quotes to acknowledge the misnomer (e.g., ‘ultra-sensitive’ mRDT).

16- The last two paragraphs of the Introduction should be rewritten to focus on clearly stating the study design and study question. As currently written details of the cohort (136-139) and study conclusions (line 146-148) should be removed, as well as the description of the “diverse and robust data”.

17- The end of the Introduction describes the data source as a randomized clinical trial, while the beginning of the Methods describes this as a “secondary analysis of a prospective cohort study”. Please clarify.

18- Please remove the “key results” icon from Table 2. Rather than color coded cells for the ND, LD, and HD cases, please use a footnote.

19- In figure 2, please describe what the shaded areas represent (95%CIs, I presume).

20- Please remove the graphical elements of Tables 3 and 4. If you wish to represent the RRs graphically, please move them to separate figures. If you choose to do so, please graphically represent the 95% CIs.

21- In the Discussion, please remove the sub-headers (e.g., “LD infection: Reservoir or Passer-by?”). Top headings (e.g., “Limitations and further research”) can remain.

22- Please rephrase the first sentence of the Discussion Conclusion: “In this study in a moderate malaria endemicity setting…”

23- At line 502, please replace “the vast majority of which being” with “likely”.

24- At line 503, please rephrase as: “Our findings suggest that implementing ultra-sensitive malaria diagnostics to detect LD infections is neither useful nor deleterious in this context.”

25- Please remove the final sentence “To endure high quality…”

26- Please check the references carefully and make sure all use the "Vancouver" style for reference formatting, and see our website for other reference guidelines https://journals.plos.org/plosmedicine/s/submission-guidelines#loc-references

It also seems that the journal name in reference 29 is misspelt.

Comments from Reviewers:

Reviewer #1: The authors have addressed all my points.

Michael Dewey

Reviewer #3: The authors have responded satisfactorily to all my comments.

I suggest that lines 79-80 in the marked up copy be restated as follows:

Every infection has a symptomatic threshold above which the magnitude of infection burden triggers fever and other clinical symptoms that distinguishes ill individuals from those who remain asymptomatic.

Reviewer #4: Thank you for addressing some of my concerns. Of my 4 suggestions regarding results the authors agreed to follow one "defining severe malaria" which has also been suggested by other reviewers. None of the suggestions regarding the discussion has resulted in text changes from what I can see, although the authors kindly explain the points I missed or must have misunderstood from their perspective. I think my suggestions would have helped the reader but they do not change the findings.

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. doi: 10.1371/journal.pmed.1003318.r005

Decision Letter 3

Thomas J McBride

13 Aug 2020

Dear Dr Hartley,

On behalf of my colleagues and the academic editor, Dr. Lorenz von Seidlein, I am delighted to inform you that your manuscript entitled "Clinical relevance of low-density Plasmodium falciparum parasitaemia in untreated febrile children: a cohort study." (PMEDICINE-D-20-00426R3) has been accepted for publication in PLOS Medicine.

PRODUCTION PROCESS

Before publication you will see the copyedited word document (in around 1-2 weeks from now) and a PDF galley proof shortly after that. The copyeditor will be in touch shortly before sending you the copyedited Word document. We will make some revisions at the copyediting stage to conform to our general style, and for clarification. When you receive this version you should check and revise it very carefully, including figures, tables, references, and supporting information, because corrections at the next stage (proofs) will be strictly limited to (1) errors in author names or affiliations, (2) errors of scientific fact that would cause misunderstandings to readers, and (3) printer's (introduced) errors.

If you are likely to be away when either this document or the proof is sent, please ensure we have contact information of a second person, as we will need you to respond quickly at each point.

PRESS

A selection of our articles each week are press released by the journal. You will be contacted nearer the time if we are press releasing your article in order to approve the content and check the contact information for journalists is correct. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact.

PROFILE INFORMATION

Now that your manuscript has been accepted, please log into EM and update your profile. Go to https://www.editorialmanager.com/pmedicine, log in, and click on the "Update My Information" link at the top of the page. Please update your user information to ensure an efficient production and billing process.

Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it.

Best wishes,

Thomas McBride, PhD

Senior Editor

PLOS Medicine

plosmedicine.org

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 STROBE checklist. STROBE, Strengthening the Reporting of Observational Studies in Epidemiology.

(DOCX)

Click here for additional data file.^{(33.8KB, docx)}

S1 Table. Results of standard mRDT and ultrasensitive mRDT stratified by ultrasensitive qPCR.

(DOCX)

Click here for additional data file.^{(14.5KB, docx)}

S2 Table. Definition of clinical failure (primary outcome measure).

Adapted from Keitel et al. [13].

(DOCX)

Click here for additional data file.^{(18.3KB, docx)}

Attachment

Submitted filename: hartley.pdf

Click here for additional data file.^{(57KB, pdf)}

Attachment

Submitted filename: UltrasensitiveMalariaDiagnostics(Hartley_09June20)_Reviewer.pdf

Click here for additional data file.^{(822KB, pdf)}

Data Availability Statement

The data set and data dictionary are available from https://github.com/epfl-iglobalhealth/Hartley2020-PLoSMedicine.

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PERMALINK

Clinical relevance of low-density Plasmodium falciparum parasitemia in untreated febrile children: A cohort study

Mary-Anne Hartley

Natalie Hofmann

Kristina Keitel

Frank Kagoro

Clara Antunes Moniz

Tarsis Mlaganile

Josephine Samaka

John Masimba

Zamzam Said

Hosiana Temba

Iveth Gonzalez

Ingrid Felger

Blaise Genton

Valérie D’Acremont

Roles

Abstract

Background

Methods/findings

Conclusions

Author summary

Why was this study done?

What did the researchers do and find?

What do these findings mean?

Introduction

Materials and methods

Design

Patient population and context

Aims

Clinical data and data collection

Laboratory procedures

Pf detection

Exposures and outcomes

Exposures

Table 1. Definition of the 3 subcohorts based on Pf parasitemia level and treatment received.

Outcomes

Statistical analyses

Epidemiology of Pf infection

Clinical presentation of Pf infection

Clinical outcomes

Controlling for bias

Missing values

Table 3. Comparative analysis of demographic and epidemiological features (ND versus LD).

Table 5. Comparative analysis of clinical presentation, lab results, and diagnoses at day zero.

Ethical considerations

Results

Cohort selection and Pf parasitemia prevalence

Population

Fig 1. Population flow chart.

Pf parasitemia prevalence

Table 2. Results of standard mRDT and ultrasensitive qPCR tests.

Distribution of Pf parasitemia in febrile children

Demographic distribution

Fig 2. Temporal and age distribution of patients with LD, HD, and ND parasitemia.

Table 4. Comparative analysis of demographic and epidemiological features (LD versus HD).

Fig 3. Distribution of severe illness and anemia between patients with LD, HD, or ND parasitemia.

Seasonal distribution

Clinical presentation of children with Pf infections

LD versus ND

Table 6. Comparative analysis of clinical presentation, lab results and diagnoses at day zero.

Fig 4. Distribution of inflammatory markers between patients with LD, HD, or ND parasitemia.

LD versus HD

Clinical outcome of children with Pf parasitemia

Clinical outcomes (LD versus ND)

Fig 5. Distribution of clinical outcomes between patients with LD, HD, or ND parasitemia.

Table 7. Comparative analysis of health outcomes.

Clinical outcomes (LD versus HD)

Table 8. Comparative analysis of health outcomes.

Discussion

Limitations and further research

Impact and recommendations

Conclusion

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0