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. 2023 Jun 14;3(6):e0002011. doi: 10.1371/journal.pgph.0002011

Clinical epidemiology of COVID-19 among hospitalized children in rural western Kenya

Adino Tesfahun Tsegaye 1,*, Christina Sherry 2, Chrisantus Oduol 3, Joyce Otieno 3, Doreen Rwigi 3, Mary Masheti 3, Irene Machura 4, Meshack Liru 5, Joyce Akuka 6, Deborah Omedo 4, Samwel Symekher 7, Samoel A Khamadi 7, Lynda Isaaka 8, Morris Ogero 8, Livingstone Mumelo 8, James A Berkley 8,9,10,11, Ambrose Agweyu 8,11, Judd L Walson 9,12, Benson O Singa 3, Kirkby D Tickell 2,9
Editor: Shivanthi Samarasinghe13
PMCID: PMC10266603  PMID: 37315023

Abstract

The epidemiology of pediatric COVID-19 in sub-Saharan Africa and the role of fecal-oral transmission in SARS-CoV-2 are poorly understood. Among children and adolescents in Kenya, we identify correlates of COVID-19 infection, document the clinical outcomes of infection, and evaluate the prevalence and viability of SARS-CoV-2 in stool. We recruited a prospective cohort of hospitalized children aged two months to 15 years in western Kenya between March 1 and June 30 2021. Children with SARS-CoV-2 were followed monthly for 180-days after hospital discharge. Bivariable logistic regression analysis was used to identify the clinical and sociodemographics correlates of SARS-CoV-2 infection. We also calculated the prevalence of SARS-CoV-2 detection in stool of confirmed cases. Of 355 systematically tested children, 55 (15.5%) were positive and were included in the cohort. The commonest clinical features among COVID-19 cases were fever (42/55, 76%), cough (19/55, 35%), nausea and vomiting (19/55, 35%), and lethargy (19/55, 35%). There were no statistically significant difference in baseline sociodemographic and clinical characteristics between SARS-CoV-2 positive and negative participants. Among positive participants, 8/55 (14.5%, 95%CI: 5.3%-23.9%) died; seven during the inpatient period. Forty-nine children with COVID-19 had stool samples or rectal swabs available at baseline, 9 (17%) had PCR-positive stool or rectal swabs, but none had SARS-CoV-2 detected by culture. Syndromic identification of COVID-19 is particularly challenging among children as the presenting symptoms and signs mirror other common pediatric diseases. Mortality among children hospitalized with COVID-19 was high in this cohort but was comparable to mortality seen with other common illnesses in this setting. Among this small set of children with COVID-19 we detected SARS-CoV-2 DNA, but were not able to culture viable SARs-CoV-2 virus, in stool. This suggests that fecal transmission may not be a substantial risk in children recently diagnosed and hospitalized with COVID-19 infection.

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of hospitalizations and deaths [1, 2] across the world. In Kenya, the first official case of COVID-19 was reported in March 2020 and by the end of November 2022, more than 341,235 people had been infected, with 5,684 deaths. However, from these data, <1% of the deaths occurred among children under the age of 15 [3]. Data from high income countries suggests that most COVID-19 cases among children and adolescents are asymptomatic or mild, although severe disease, including multisystem inflammatory syndrome (MIS), may develop [4–6]. In resource-limited settings, where children have a higher prevalence of comorbidities, including malnutrition, HIV and other infections, COVID-19 management maybe more complicate and may have worse clinical outcomes [7]. However, there are limited data on the epidemiologic profile, diagnosis and risk factors for COVID-19 among pediatric patients in resource-limited settings.

Fever and cough are the most frequently reported clinical features in pediatric COVID-19, but diarrhea is also a common manifestation [8–10]. The symptomatic overlap of COVID-19 with other prevalent diseases in resource-limited settings, including diarrheal disease, malaria and pneumonia, may make the syndromic identification of COVID-19 challenging [11–14]. Polymerase Chain Reaction (PCR) testing from nasopharyngeal samples or saliva is the gold standard for COVID-19 diagnosis but is often unavailable or not systematically collected in acutely ill children in low resource settings. In addition, several studies have reported the detection of SARs-CoV-2 in stool samples [15–17], highlighting that feco-oral transmission may be an important mode of transmission, particularly in low resource settings where access to adequate sanitation and clean water may be limited [18–20].

We sought to identify clinical and sociodemographic correlates of COVID-19 among hospitalized children in Kenya and to evaluate PCR and culture-based detection of SARS-CoV-2 in fecal samples as a measure of the potential for fecal transmission.

Methods

Study design, setting, and population

This study was conducted during the third wave of COVID-19 in Kenya when the B.1.1.7 (Alpha) was the dominant variant [21, 22]. We systematically tested all children admitted to three hospitals in Kenya (Homa Bay County Referral, Kisii Teaching and Referral, and Migori County Referral hospitals), who were aged two months to 15 years for SARs CoV-2 between March 1 and June 30, 2021. Systematic testing excluded suspected COVID-19 cases who had already been at the study hospital for more than 24 hours or were referred after 24 hours of admission to another hospital, as these children may have acquired the infection during their hospitalization. Baseline clinical and sociodemographic data were collected from all patients prior to SARs CoV-2 testing.

Confirmed cases were enrolled in a prospective cohort study of hospitalized children aged two months to 15 years if they planned to remain within the hospital catchment area for at least six months, and consented to participate in the study. Cohort participants were followed daily during hospitalization and monthly for 6-months after hospital discharge.

Participants were scheduled for monthly follow-up visits in the outpatient clinics, unless the participant was hospitalized at the time of the visit. When in-person visits were not possible, interviews were conducted through a phone call and participants’ vital status was recorded. Anthropometric measurements were only done at in-person follow-up visits. Follow-up ended when the child completed their six-month follow-up visit or when a child died. Families that missed the 6-month visit and were not traceable via phone calls or home visits were declared lost to follow up. Nasopharyngeal swab, rectal swab, stool, and blood samples were taken at admission.

Study outcomes

The primary outcomes of this study were the clinical profile and correlates of SARS-CoV-2 infection and its detection by PCR and culture in stool or rectal swab samples. Secondary outcomes include the mortality rate among cohort participants.

Statistical analysis

Descriptive statistics summarizes distribution of variables between confirmed COVID-19 cases and children who were not infected. A chi-square test was used to evaluate the relationship between COVID-19 status and categorical variables, and a t-test was used for continuous variables. We selected possible clinical and sociodemographic correlates of SARS-CoV-2 infection a priori based on previously published literature [21–23]. The clinical variables were sickle cell disease, fever, lethargy, vomiting/nausea, difficulty of breathing, convulsion, diarrhea, cough, headache, not feeding, abdominal pain, fatigue, reduced air entry, wheeze, chest indrawing, crackles, capillary refill, activity (mental status of being irritable/Agitated or lethargic), and jaundice. The sociodemographic characteristics were age, sex, nutritional status (wasting measured by mid-upper arm circumference (MUAC), weight for height Z score (WHZ), and body mass index (BMI), and stunting), breastfeeding, birth order, caregiver marital status, and caregiver educational status. We used logistic regression to evaluate the association of each variable with SARS-CoV-2 infection. In addition, we explored the frequency of mortality and its distribution across key clinical correlates.

Materials and techniques for stool sample processing

SARS-CoV-2 was detected in stool and rectal swab samples using PCR and viral culture. Initially, 180-220mg of swab /stool was placed in an Eppendorf tube, where 1 ml of the swab/stool lysis buffer was added to the fecal sample and was further processed. Quantitative Real-Time PCR (qRT-PCR) was carried out using primers and probes from the Da An SARSCoV-2 detection kit. This kit detects the presence of SARS-CoV-2 ORF-1ab and N genes explicitly. The real-time PCR was repeated using another kit, specifically testing the ‘reactive’ sample. In addition, the PCR-positive samples were further processed and inoculated to the cell line (Vero-E6) for isolation and detection of a live virus and followed up for a week at 35°C. To reliably determine the isolation of the virus from fecal samples, the samples were re-inoculated in the same cell lines and incubated for an additional 10–12 days. RNA was extracted using the RADI Nucleic Acid Extraction protocol and tested for the presence of the virus using the Sansure Biotech Novel Coronavirus (2019-nCoV) diagnostic kit. The kit contains specific primers and probes for detecting the SARS-CoV-2 largest gene (ORF1ab) and the nucleocapsid (N) gene regions. Where both whole stool and rectal swabs were available, both sample types were tested to maximize the chance of isolating live fecal virus [23].

Ethics

Ethical approval was obtained from the University of Washington Insitutional Review Board and all participating institutions. Written consent was obtained from caregivers of all study participants.

Results

A total of 355 children screened, and 55 (16%) were SARS CoV-2 positive and enrolled in the cohort. In addition, 296 (83%) tested negative for SARS CoV-2 and 4 (1%) had an inconclusive test result (Fig 1).

Fig 1. Flow chart.

Fig 1

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Most participants were over two years old (216, 61%), a quarter (80, 23%) had severe wasting, 49 (14%) had severe stunting, and 6 (2%) were HIV infected. Among the 139 children aged less than 2 years, 71 (51%) were breastfeeding, and out of 28 children aged less than 6 months, 7 (25%) were exclusively breastfeeding (Table 1).

Table 1. Baseline characteristics of participants.

Characteristic Overall, N = 3551 COVID-19 Negative, N = 3001 COVID-19 Positive, N = 551
Study Hospital
 Homa Bay 42 (12%) 27 (9.0%) 15 (27%)
 Kisii 85 (24%) 73 (24%) 12 (22%)
 Migori 228 (64%) 200 (67%) 28 (51%)
Age
 <6 months 28 (7.9%) 25 (8.3%) 3 (5.5%)
 6–11 months 40 (11%) 32 (11%) 8 (15%)
 12–23 months 71 (20%) 58 (19%) 13 (24%)
 2–5 years 123 (35%) 108 (36%) 15 (27%)
 > = 5 years 93 (26%) 77 (26%) 16 (29%)
Sex
 Female 161 (45%) 130 (43%) 31 (56%)
 Male 194 (55%) 170 (57%) 24 (44%)
Nutritional status
 No Malnutrition 230 (65%) 190 (64%) 40 (73%)
 MAM 43 (12%) 40 (13%) 3 (5.5%)
 SAM 80 (23%) 68 (23%) 12 (22%)
 Unknown 2 2 0
Stunting
 Severe stunting 49 (14%) 42 (14%) 7 (13%)
 Moderate stunting 41 (12%) 35 (12%) 6 (11%)
 No stunting 255 (74%) 214 (74%) 41 (76%)
 Unknown 10 9 1
Breastfeeding status
 Exclusive breastfeeding 66 (19%) 56 (19%) 10 (18%)
 Non-exclusive breastfeeding 11 (3.1%) 7 (2.3%) 4 (7.3%)
 Not breastfeeding 278 (78%) 237 (79%) 41 (75%)
Cerebral palsy 19 (5.4%) 17 (5.7%) 2 (3.6%)
Sickle cell disease 18 (5.1%) 14 (4.7%) 4 (7.3%)
HIV infection 6 (1.7%) 6 (2.0%) 0 (0%)
Birth order
 First 83 (23%) 70 (23%) 13 (24%)
 Second 87 (25%) 71 (24%) 16 (29%)
 Third and above 185 (52%) 159 (53%) 26 (47%)
Caregiver age
 <18 Years 1 (0.3%) 1 (0.3%) 0 (0%)
 > = 18 Years 339 (95%) 286 (95%) 53 (96%)
 >50 Years 13 (3.7%) 11 (3.7%) 2 (3.6%)
 Care home or unclear 2 (0.6%) 2 (0.7%) 0 (0%)
Caregiver marital status
 Married 295 (83%) 250 (83%) 45 (82%)
 Unmarried 59 (17%) 49 (16%) 10 (18%)
 NA 1 (0.3%) 1 (0.3%) 0 (0%)
Caregiver educational status
 None 21 (5.9%) 16 (5.3%) 5 (9.1%)
 Primary 215 (61%) 180 (60%) 35 (64%)
 Secondary 87 (25%) 77 (26%) 10 (18%)
 Above secondary 30 (8.5%) 25 (8.3%) 5 (9.1%)
 Unknown/NA 2 (0.6%) 2 (0.7%) 0 (0%)
Primary caregiver
 Biological Mother 324 (91%) 272 (91%) 52 (95%)
 Other 31 (8.7%) 28 (9.3%) 3 (5.5%)
Known household COVID-19 contact 6 (1.7%) 6 (2.0%) 0 (0%)
Respiratory rate 34 ± 9 34 ± 9 33 ± 9
Heart rate 123 ± 24 123 ± 23 121 ± 25
Temperature 36.8 ± 0.7 36.8 ± 0.8 36.7 ± 0.5
Oxygen saturation
 <90% 31 (8.7%) 24 (8.0%) 7 (13%)
 > = 90% 324 (91%) 276 (92%) 48 (87%)
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1n (%); Mean (SD)

Clinical features of COVID-19

The most frequent clinical feature among COVID-19 infected children was fever (42, 76%), followed by cough (19, 35%), nausea and vomiting (19, 35%), and lethargy (19, 35%). The distribution of baseline sociodemographic and clinical characteristics was not statistically significantly different between COVID-19 infected and non-infected participants.

In the bivariable analysis, we observed a lower risk (marginally non-significant) of COVID-19 among males as compared to females (Crude Odds Ratio (COR): 0.59 (95%CI: 0.33, 1.05), p-value = 0.075) and among those who reported a headache compared to those who did not (COR: 0.34 (95%CI: 0.08, 0.98), p-value = 0.08) (Table 2).

Table 2. Logistic regression table for the correlates of COVID-19 infection.

Characteristic N 0, N = 2961 1, N = 551 COR2 95% CI2 p-value
Age 351
<6 months 25 (8.4%) 3 (5.5%) — —
6–11 months 31 (10%) 8 (15%) 2.15 0.56, 10.6 0.3
12–23 months 57 (19%) 13 (24%) 1.9 0.55, 8.81 0.3
2–5 years 107 (36%) 15 (27%) 1.17 0.35, 5.32 0.8
> = 5 years 76 (26%) 16 (29%) 1.75 0.53, 7.98 0.4
Sex 351
Female 128 (43%) 31 (56%) — —
Male 168 (57%) 24 (44%) 0.59 0.33, 1.05 0.075
Birth order 351
First 70 (24%) 13 (24%) — —
Second 70 (24%) 16 (29%) 1.23 0.55, 2.79 0.6
Third and above 156 (53%) 26 (47%) 0.9 0.44, 1.90 0.8
Caregiver marital status 351
Married 246 (83%) 45 (82%) — —
Unmarried 50 (17%) 10 (18%) 1.09 0.49, 2.24 0.8
Caregiver educational status 350
Above secondary 24 (8.1%) 5 (9.1%) — —
None 16 (5.4%) 5 (9.1%) 1.5 0.36, 6.23 0.6
Primary 180 (61%) 35 (64%) 0.93 0.36, 2.92 0.9
Secondary 75 (25%) 10 (18%) 0.64 0.21, 2.22 0.5
Nutritional status 349
No Malnutrition 189 (64%) 40 (73%) — —
MAM 40 (14%) 3 (5.5%) 0.35 0.08, 1.04 0.1
SAM 65 (22%) 12 (22%) 0.91 0.44, 1.81 0.8
Breastfeeding 351
Exclusive breastfeeding 56 (19%) 10 (18%) — —
Non-exclusive breastfeeding 7 (2.4%) 4 (7.3%) 3.2 0.73, 12.8 0.1
Non-breast feeding 233 (79%) 41 (75%) 0.99 0.48, 2.19 >0.9
Known sickle cell disease 351 14 (4.7%) 4 (7.3%) 1.58 0.43, 4.61 0.4
Fever 351 228 (77%) 42 (76%) 0.96 0.50, 1.96 >0.9
Headache 351 43 (15%) 3 (5.5%) 0.34 0.08, 0.98 0.08
Vomiting/Nausea 351 81 (27%) 19 (35%) 1.4 0.75, 2.56 0.3
Diarrhea <14 days 351 46 (16%) 9 (16%) 1.06 0.46, 2.23 0.9
Abdominal pain 142 54 (43%) 4 (24%) 0.4 0.11, 1.22 0.13
Not feeding 351 19 (6.4%) 7 (13%) 2.13 0.79, 5.13 0.11
Cough <14 days 351 113 (38%) 19 (35%) 0.85 0.46, 1.55 0.6
Difficulty of breathing 153 59/132 (45%) 8/21 (38%) 0.76 0.28, 1.93 0.6
Fatigue 351 57 (19%) 12 (22%) 1.17 0.56, 2.30 0.7
Lethargy 351 98 (33%) 19 (35%) 1.07 0.57, 1.94 0.8
Convulsion 351 31 (10%) 5 (9.1%) 0.85 0.28, 2.13 0.8
Activity 351
Irritable/Agitated 22 (7.4%) 4 (7.3%) — —
Lethargic 47 (16%) 12 (22%) 1.4 0.43, 5.47 0.6
Normal 227 (77%) 39 (71%) 0.94 0.34, 3.36 >0.9
Jaundice 351 38 (13%) 3 (5.5%) 0.39 0.09, 1.14 0.13
Reduced air entry 351 27 (9.1%) 5 (9.1%) 1 0.33, 2.51 >0.9
Wheeze 351 37 (12%) 4 (7.3%) 0.55 0.16, 1.44 0.3
Chest indrawing 351 28 (9.5%) 7 (13%) 1.4 0.54, 3.22 0.5
Crackles 351 38 (13%) 4 (7.3%) 0.53 0.15, 1.40 0.2
Capillary refill 351
<2 Seconds 138 (47%) 30 (55%) — —
2–3 Seconds 133 (45%) 21 (38%) 0.73 0.39, 1.33 0.3
>3 Seconds 25 (8.4%) 4 (7.3%) 0.74 0.21, 2.07 0.6
Hemoglobin 334 8.54+/-2.77 9.27+/-2.90 1.1 0.99, 1.22 0.08
WBC 334 15+/-11 13+/-10 0.99 0.96, 1.02 0.4
RBC 333 3.49+/-1.33 3.80+/-1.28 1.19 0.96, 1.48 0.11
Platelets 332 244+/-187 216+/-148 1 1.00, 1.00 0.3
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1n (%)

2OR = Odds Ratio, CI = Confidence Interval

Outcomes of the cohort

In the cohort, 8/55 (15%) of the participants died before the end of the 180-day follow-up period, with seven of the eight deaths occurring prior to hospital discharge (7/55–12.7% [95% CI: 5.3, 24.5%]). The remaining death occurred after the third month of follow-up (Fig 2). Four of the eight children who died were below 2 years of age at enrolment and three were above five years of age. Of the children who died, five had severe acute malnutrition, three had severe stunting and one had cerebral palsy. At admission, four were lethargic, three were not feeding, four had a fever, three had a cough, and three had nausea and vomiting.

Fig 2. Kaplan Meier survival curve of children with confirmed COVID-19.

Fig 2

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Fecal shedding of SARS-CoV-2

Of the 55 children with COVID-19, 53 had stool and/or rectal swabs collected at enrolment; 49 children had a rectal swab and 38 had whole stool samples. Overall, 9 (17%) of these children had a positive PCR for COVID-19 from stool or rectal swab (Table 3), with 5 (10%) positive results from rectal swabs and 8 (21%) from whole stool. Four children had SARS-CoV-2 detected in both sample types at enrolment. None of the PCR-positive rectal swabs or stool samples was culture positive, despite repeat attempts to culture both stool and rectal swabs. The clinical profiles of children with stool and/or rectal samples collected are given by PCR result in Table 3.

Table 3. Differences in clinical profile between stool/rectal swab positive and negative participants.

Characteristic N Stool/rectal swab PCR negative, N = 441 Stool/rectal swab PCR positive, N = 91
General clinical characteristics
 Fever 53 35 (80%) 7 (78%)
 Fatigue 53 8 (18%) 4 (44%)
 Headache 53 3 (6.8%) 0 (0%)
 Not feeding 53 5 (11%) 1 (11%)
 Oxygen saturation 53 94.9 +/-7.2 98.0 +/-1.4
 Temperature 53 36.72 +/-0.50 36.68 +/-0.34
Respiratory
 Cough <14 days 53 17 (39%) 0 (0%)
 Difficulty of breathing 20 7 (41%) 0 (0%)
 Chest indrawing 53 6 (14%) 0 (0%)
 Reduced air entry 53 4 (9.1%) 0 (0%)
 Wheeze 53 4 (9.1%) 0 (0%)
 Crackles 53 4 (9.1%) 0 (0%)
 Respiratory rate 53 33 +/-9 29 +/-4
Gastrointestinal
 Diarrhea <14 days 53 7 (16%) 1 (11%)
 Vomiting/Nausea 53 17 (39%) 1 (11%)
 Abdominal pain 17 4 (29%) 0 (0%)
 Jaundice 53 3 (6.8%) 0 (0%)
Neurological symptoms
 Lethargy 53 15 (34%) 3 (33%)
 Convulsion 53 5 (11%) 0 (0%)
 Activity 53
 Irritable/Agitated 2 (4.5%) 2 (22%)
 Lethargic 8 (18%) 3 (33%)
 Normal 34 (77%) 4 (44%)
Circulatory
 Capillary refill 53
 <2 Seconds 28 (64%) 2 (22%)
 2–3 Seconds 13 (30%) 7 (78%)
 >3 Seconds 3 (6.8%) 0 (0%)
 Heart rate 53 119 +/-26 132 +/-21
 Hemoglobin 53 9.43 +/-2.98 8.68 +/-2.31
 WBC 53 12 +/-6 23 +/-18
 RBC 53 3.87 +/-1.30 3.54 +/-1.02
 Platelet 53 214 +/-147 255 +/-152
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1n (%)

Discussion

In western Kenya, fever, cough, nausea and vomiting, and lethargy were the most frequent signs and symptoms observed among children testing positive for COVID-19. However, there was no difference in the sociodemographic and clinical characteristics of children with confirmed COVID-19 in comparison to those children who tested negative for COVID-19. This finding highlighting the challenges clinicians face in identifying children with COVID-19 in the absence of laboratory confirmatory testing, particularly given the overlap of these non-specific symptoms with other common illnesses frequently presenting to hospital [24–30].

In this study, 14% of the children with COVID-19 died, and all but one death occurred during initial hospitalization. A recent study by Nachega et al. in six African countries, reported that 8.3% of children with COVID-19 died, while a similar study from Brazil among children and adolescents below age <20 reported a 7.6% mortality rate during hospital admission [24, 31]. These findings are consistent with the mortality rate observed in our study. Importantly, five of the eight deaths observed were among children with severe wasting. Children with COVID-19 appear to have similar mortality risk to children with other common medical conditions resulting in hospital admission in sub-Saharan Africa [32, 33].

Evidence from high-income countries suggests that COVID-19-related mortality among hospitalized children and adolescents is less than 5% [28, 34–36], considerably lower than that observed in this study. This disparity is likely to be related to higher capacity of health facilities to care for acute unwell children and the lower prevalence of comorbidities such as wasting and stunting in high income countries. Efforts to address existing comorbidities and strengthen health systems in low resource settings are urgently needed to reduce mortality, not only from COVID-19 but from other common pediatric conditions observed in these settings.

Only a quarter (27%) of children testing positive for COVID-19 by PCR from nasopharyngeal swabs had PCR-detectable SARS-CoV-2 in either stool or rectal swabs. Despite evidence that SARS-CoV-2 can infect the intestine and cause inflammation and gastrointestinal symptoms, children in this study with positive stool PCR tests did not have more reported diarrhea than COVID-19 negative children [37–39]. A recent systematic review and meta-analysis evaluated the performance of COVID-19 PCR detection in adults and reported that stool sample or rectal swab PCR tests have a sensitivity of 24% (16.7%, 33.0%), as opposed to a sensitivity of 73% when using nasopharyngeal swab samples [16]. A similar meta analysis that included children and adults, found that 25% of individuals with positive nasopharyngeal samples had a positive stool PCR test, and that this proportion did not differ between age groups [18]. In contrast, a third systematic review reported that SARS-CoV-2 could be detected in 75% of stool samples collected from children with COVID-19 [40]. There is clearly heterogeneity in the proportion of COVID-19 cases who have PCR-detectable SARS-CoV-2 in their stool, which may be related to timing of sample collection relative to infection or severity of infection, variant of virus, or other host factors. Interestingly, despite repeated efforts using both whole stool and rectal swabs, we were not able to culture viable virus from any fecal sample in this study. Similarly low isolation rates have been observed in studies form China, Germany, Korea and Singapore [41, 42], suggesting that across these diverse settings there may be limited viable virus shed in stool and that fecal shedding of SARS-CoV-2 may not be a major route of transmission.

This study had notable strengths, particularly the systematic screening for SARs CoV-2, the long duration of follow-up, and the extensive efforts to culture live virus from stool. However, the study had a relatively small sample size and the observational nature of the study limits our ability to infer causality. Secondly, the study was conducted in a hospital setting and these results may not be generalizable to children living in the community. Finally, due to isolation protocols and a high rate of early mortality, we were unable collect whole stool or rectal swab samples on a small number of children, which may have introduced a degrees of selection bias.

Conclusion

The non-specific nature of the signs and symptoms associated with COVID-19 in children make it difficult to differentiate from other common pediatric infections in sub-Saharan Africa. This poses a particular challenge in resource-limited settings where diagnostics are often unavailable or unaffordable. Mortality among children hospitalized with COVID-19 was high, but appears comparable to mortality observed among children hospitalized for other causes in the region. SARs CoV-2 was only detected in stool or rectal swabs by PCR in a quarter of children with confirmed COVID- 19 infection and live virus was not detected in any fecal samples. These data suggest that fecal transmission may not play a substantial role in the transmission of the virus.

Supporting information

S1 Text. Completed inclusivity questionnaire.

(DOCX)

Click here for additional data file. (65.3KB, docx)
S1 Data. Data underlying the study findings.

(CSV)

Click here for additional data file. (835.5KB, csv)
S1 Checklist. Completed STROBE checklist.

(DOCX)

Click here for additional data file. (39.7KB, docx)

Acknowledgments

The authors would like to acknowledge the support of the Bill & Melinda Gates Foundation (INV016894), and the participants of this research. For the purpose of open access, a Creative Commons Attribution is applied under the grant conditions of the Foundation for any author-accepted manuscript version arising from this submission.

Data Availability

All data in Supporting information files.

Funding Statement

JLW received the grant from Bill & Melinda Gates Foundation [INV016894] (https://www.gatesfoundation.org/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0002011.r001

Decision Letter 0

Shivanthi Samarasinghe

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

11 Apr 2023

PGPH-D-23-00293

Clinical epidemiology of COVID-19 among hospitalized children in rural western Kenya

PLOS Global Public Health

Dear  Corresponding Author,

Thank you for submitting your manuscript to PLOS Global Public Health. After careful consideration, we feel that it has merit but does not fully meet PLOS Global Public Health’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

Kind regards,

Shivanthi Samarasinghe, PhD

Academic Editor

PLOS Global Public Health

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Reviewer #1: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Tsegaye et al. describe the clinical characteristics and associations with COVID-19 among hospitalized children near Kisumu, Kenya. This well-written manuscript represents multiple important contributions, including lack of culturable SARS-CoV-2 in stool from hospitalized children, and similar demographic and clinical characteristics in hospitalized children regardless of SARS-CoV-2 status.

A CONSORT diagram could help to show who was included and excluded from analysis for different reasons, and who was followed-up to ascertain survival.

It appears only a small fraction (53 out of >300) children were able to be followed-up to ascertain outcomes. Could the authors comment on potential biases due to the strong down-selection of who was followed-up?

At the end of the paper, the authors note that survival in the SARS-CoV-2 PCR+ cohort is similar to survival rates reported in SARS-CoV-2 negative children admitted to hospitals in this region. Do the authors have access to SARS-CoV-2 negative or overall child survival data in order to make a comparison? It would be interesting to know if observed mortality rates differ by SARS-CoV-2 status, and this might enable the authors to make a stronger point about children dying of other causes.

These are just minor suggestions – overall, very clear and interesting work!

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Reviewer #1: Yes: Anna Bershteyn

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0002011.r003

Decision Letter 1

Shivanthi Samarasinghe

22 May 2023

Clinical epidemiology of COVID-19 among hospitalized children in rural western Kenya

PGPH-D-23-00293R1

Dear Corresponding Author,

The manuscript describes the clinical characteristics and associations with COVID-19 among hospitalized children near Kisumu, Kenya, which is relevant and timely to the scope of the journal.

We are pleased to inform you that your manuscript 'Clinical epidemiology of COVID-19 among hospitalized children in rural western Kenya' has been provisionally accepted with minor revisions for publication in PLOS Global Public Health.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Global Public Health.

Best regards,

Shivanthi Samarasinghe, PhD

Academic Editor

PLOS Global Public Health

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Reviewer Comments (if any, and for reference):

Associated Data

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

    Supplementary Materials

    S1 Text. Completed inclusivity questionnaire.

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    Click here for additional data file. (65.3KB, docx)
    S1 Data. Data underlying the study findings.

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    Data Availability Statement

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