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PLOS Neglected Tropical Diseases logoLink to PLOS Neglected Tropical Diseases
. 2023 Sep 1;17(9):e0011593. doi: 10.1371/journal.pntd.0011593

Direct mosquito feedings on dengue-2 virus-infected people reveal dynamics of human infectiousness

Louis Lambrechts 1,*,#, Robert C Reiner Jr 2,*,#, M Veronica Briesemeister 3, Patricia Barrera 3,4, Kanya C Long 5, William H Elson 3, Alfonso Vizcarra 3, Helvio Astete 6,7, Isabel Bazan 6, Crystyan Siles 6, Stalin Vilcarromero 6,¤a, Mariana Leguia 4, Anna B Kawiecki 8, T Alex Perkins 9, Alun L Lloyd 10, Lance A Waller 11, Uriel Kitron 12, Sarah A Jenkins 6,¤b, Robert D Hontz 6,¤c, Wesley R Campbell 6,¤d, Lauren B Carrington 13, Cameron P Simmons 14, J Sonia Ampuero 6, Gisella Vasquez 7, John P Elder 15, Valerie A Paz-Soldan 16, Gonzalo M Vazquez-Prokopec 12, Alan L Rothman 17, Christopher M Barker 8, Thomas W Scott 3,, Amy C Morrison 8,
Editor: Elvina Viennet18
PMCID: PMC10501553  PMID: 37656759

Abstract

Dengue virus (DENV) transmission from humans to mosquitoes is a poorly documented, but critical component of DENV epidemiology. Magnitude of viremia is the primary determinant of successful human-to-mosquito DENV transmission. People with the same level of viremia, however, can vary in their infectiousness to mosquitoes as a function of other factors that remain to be elucidated. Here, we report on a field-based study in the city of Iquitos, Peru, where we conducted direct mosquito feedings on people naturally infected with DENV and that experienced mild illness. We also enrolled people naturally infected with Zika virus (ZIKV) after the introduction of ZIKV in Iquitos during the study period. Of the 54 study participants involved in direct mosquito feedings, 43 were infected with DENV-2, two with DENV-3, and nine with ZIKV. Our analysis excluded participants whose viremia was detectable at enrollment but undetectable at the time of mosquito feeding, which was the case for all participants with DENV-3 and ZIKV infections. We analyzed the probability of onward transmission during 50 feeding events involving 27 participants infected with DENV-2 based on the presence of infectious virus in mosquito saliva 7–16 days post blood meal. Transmission probability was positively associated with the level of viremia and duration of extrinsic incubation in the mosquito. In addition, transmission probability was influenced by the day of illness in a non-monotonic fashion; i.e., transmission probability increased until 2 days after symptom onset and decreased thereafter. We conclude that mildly ill DENV-infected humans with similar levels of viremia during the first two days after symptom onset will be most infectious to mosquitoes on the second day of their illness. Quantifying variation within and between people in their contribution to DENV transmission is essential to better understand the biological determinants of human infectiousness, parametrize epidemiological models, and improve disease surveillance and prevention strategies.

Author summary

In this study, we examined the potential for people with mild illness to transmit dengue virus to mosquitoes. Although people with mild dengue illness can be infectious, they often are undetected by surveillance systems and research teams. Variation in infectiousness over the course of a person’s infection is largely unexplored, but potentially important component of dengue epidemiology. In an effort to better understand the factors that underlie this variation, we blood fed laboratory-reared, uninfected mosquitoes directly on mildly ill people naturally infected with dengue virus in Iquitos, Peru. Detection of virus in mosquito saliva after feeding on an infected person was considered positive for mosquito transmission. As has been reported previously, transmission to mosquitoes was positively associated with the amount of virus in a person’s blood and the number of days after the mosquito fed on an infected person. Unlike results from previous studies, which reported peak transmission during the first day of a person’s illness, we found that for mildly ill people infectiousness to mosquitoes peaked on the second day of illness. Because people with mild illness are thought to contribute more to dengue virus transmission than more severely ill people, subtle differences in the dynamics of their infectiousness to mosquitoes could be epidemiologically significant.

Introduction

Dengue is one of the fastest-growing global infectious diseases [1]. It is now endemic in an increasing number of tropical cities and its geographical range is expected to further expand due to ongoing global phenomena including urbanization and climate change [24]. There are an estimated 400 million yearly human dengue virus (DENV) infections, of which approximately 100 million are apparent with symptoms [5]. Dengue is a self-limited infection with a broad range of clinical manifestations ranging from asymptomatic infection to life-threatening illness [6]. Although people without any clinical manifestations or with mild symptoms can be infectious, they usually go undetected by the healthcare systems and thus constitute a considerable challenge to disease surveillance and control [7,8]. Understanding variation within and between people in their contribution to onwards virus transmission is essential to improve the theory of DENV epidemiology, lead to innovation in outbreak detection and response, and refine assessments of prevention strategies [9].

The mosquito, Aedes aegypti, is the principal DENV vector and a primary driver of the increasing disease burden and expanding geographic distribution of dengue [1,10]. After an Ae. aegypti female takes a blood meal from a viremic human, virus transmission can happen if the virus successfully infects and replicates in the mosquito’s midgut epithelium, crosses the midgut basal lamina, infects and replicates in the salivary glands, and is released in saliva as the mosquito bites another person. This process is generally represented by two distinct epidemiological parameters. Vector competence refers to the physiological ability of a mosquito to become infected and subsequently transmit the virus, whereas the extrinsic incubation period (EIP) represents the typical duration of this process [11]. It is well established that DENV vector competence is positively correlated with the virus dose ingested in the blood meal [7,1216]. Human infectiousness to mosquitoes roughly follows the kinetics of viremia, and symptomatic people can be infectious to mosquitoes from two days before to six days after the onset of symptoms [7,1214,16,17]. Although human-to-mosquito DENV transmission is primarily determined by the magnitude of viremia, laboratory experiments indicate that vector competence and EIP also vary as a function of other factors such as the mosquito genotype, the virus strain, and the ambient temperature [1823].

Several studies point to human factors other than viremia that influence DENV infectiousness to mosquitoes. A hospital-based study in Vietnam found that rising levels of DENV-specific antibodies were associated with a reduced likelihood of human-to-mosquito transmission independently of viremia [16]. A community-based study in Cambodia reported that asymptomatic and presymptomatic people were more infectious to mosquitoes than symptomatic people at the same level of viremia [7]. In laboratory studies, low-density lipoproteins [24,25] and serum iron [26] were shown to inhibit DENV acquisition by Ae. aegypti whereas blood glucose [27] and DENV non-structural protein 1 (NS1) antigenemia [28] enhanced mosquito infection. The blood concentration of some of these metabolites are known to vary within and between DENV-infected people [29,30] and could contribute to variation in DENV infectiousness to mosquitoes.

Regardless of the underlying mechanisms, knowledge of DENV transmission from humans to mosquitoes is epidemiologically imprecise and potentially misleading because it does not account for such variation in infectiousness within and between different people. This knowledge gap is due in large part to the logistical challenge of quantifying human-to-mosquito DENV transmission in a natural setting [31]. Here, we conducted a field-based study to characterize the temporal dynamics of viremic human infectiousness to mosquitoes with an emphasis on the difficult-to-study people with mild disease. Even though people with mild disease make up the bulk of human DENV infections, they are often missed by public health surveillance systems because surveillance programs are designed to identify infections in people who are ill enough to seek medical treatment [5]. We analyzed a dataset newly generated from a study design that we previously developed to identify DENV-infected volunteers with mild illness and then carried out direct mosquito feedings on those individuals [9,15,32]. Although our study focus was dengue, we also enrolled Zika virus (ZIKV)-infected participants during the study period when ZIKV circulated in Iquitos.

Methods

Ethics statement

The study protocol was approved by the U.S. Naval Medical Research Unit No. 6 (NAMRU-6) Institutional Review Board (Protocol Number NAMRU6.2014.0028), which includes Peruvian representation and complies with U.S. Federal and Peruvian regulations governing the protection of human subjects. Institutional Review Board authorization agreements were established between the U.S. NAMRU-6 and all participating institutions. The protocol was reviewed and approved by the Loreto Regional Health Department, which oversees health research in Iquitos. Written informed consent was obtained from all adult participants and the parents or guardians of all the child participants between 5–17 years. Participants that were minors provided assent (written for 8- to 17-years old, verbal for <8 years old).

Study design and sample testing

Study area and period

Iquitos is an urban center of ~400,000 inhabitants located in the Amazon Basin of northeastern Peru that functions almost as a self-contained epidemiological system because access to it is limited to air and river travel. The study area was previously described in detail [9]. DENV is endemic in Iquitos with a strong seasonal pattern. In general, DENV transmission is low from May to July, increases in August and September, and usually peaks between November and January. Our study was conducted from June 2015 to April 2019. In May 2016, the first human ZIKV infections were reported in Iquitos. ZIKV transmission continued through April 2017 with almost no detection of DENV during that time period.

Study protocol

The overall study design and procedures are described in detail by Morrison et al. [9]. Briefly, DENV and ZIKV cases were identified from two ongoing community-based cohort studies (~20,000 people with 3–5 febrile illness surveillance visits per week) initiated in June 2015 and from passive clinic-based disease surveillance carried out daily in approximately 6 facilities [33]. People identified with active DENV and ZIKV infections (i.e., detectable viremia) were invited to participate. Participation consisted of (1) direct mosquito feeding, (2) collection of venous blood samples, (3) health monitoring, and (4) symptom and movement questionnaires [9]. Study procedures were repeated daily if the participant’s blood from the previous day tested positive for DENV or ZIKV and the participant agreed to continue. Participants could decline individual procedures on individual days and remain in the study.

Participant testing

Blood samples were generally tested within 24 hours of collection by reverse transcription quantitative PCR (RT-qPCR) for DENV and ZIKV RNA (see sample testing section below). As soon as results were available, study subjects who tested positive for DENV or ZIKV and had indicated willingness to participate in the viremic participant protocol were contacted and enrolled to perform the mosquito feeding and sequential blood sample collection procedures. During the ZIKV transmission period, Institutional Review Board permission was obtained to initiate the ZIKV-positive case protocol prior to obtaining the initial RT-qPCR result to maximize the probability of detecting human-to-mosquito transmission, because ZIKV-positive participants tended to be afebrile and were identified when they developed a rash. Participants were informed of their infection status within 12–24 hours and virus-positive participants were invited to repeat the mosquito feeding, blood sampling, and questionnaire procedures. Laboratory results were provided to study participants with an explanation by study personnel.

Mosquitoes

Human infectiousness was experimentally assessed using laboratory-reared mosquitoes derived from the local, wild-type Ae. aegypti population. To minimize uncontrolled differences between experiments and maintain a level of genetic diversity representative of the wild mosquito population, a genetically diverse laboratory strain (GDLS) was created as previously described [9,34,35]. Briefly, the GDLS was established between August and December 2015 by collecting ~1,000 immature Ae. aegypti at each of 10 locations across Iquitos. Wild female progenitors were screened by RT-qPCR for DENV, the only known Aedes-borne virus circulating in Iquitos at the time, before hatching their eggs. None of the field-caught progenitors tested positive for DENV RNA. The 10 strains were maintained separately and merged to generate the GDLS mosquitoes used in blood-feeding experiments. All experiments were conducted within the first 6 generations of the GDLS. Virus-free mosquitoes were maintained in a field insectary constructed in a local household with a relative humidity (RH) of 70–80% and a temperature of approximately 27–28°C. The insectary had windows that let in natural light and room lights were turned on from approximately 0800 to 1700 each day. The natural photoperiod in Iquitos averages 12 hour:12 hour light:dark and variation between minimum and maximum daylight is approximately 1 hour. Mosquitoes that fed on viremic participants were held in a secure, laboratory-based insectary under the same temperature, RH, and light conditions. The GDLS mosquitoes were maintained with weekly non-infectious blood meals (chicken blood available for sale from a local butcher) through an artificial membrane. Resulting eggs were hatched in a water/tea (Collins Cinnamon tea) infusion (1 liter) for 24 hours. Two-hundred larvae per liter of tap water were placed in white 26.5 × 16.5 cm plastic pans. Larvae were provided a combination of wheat powder mixed with commercial fish food daily until pupation. Pupae were transferred to 1-pint plastic containers and placed into 1-gallon cardboard cages, provided with a moist towel to maintain humidity, a sugar cube, and a water pledget on top of the cages. As the mosquitoes emerged, females were separated into 1-pint cardboard cages containing 25 female Ae. aegypti each and 5 males to allow for mating. The workflow was adjusted to ensure that sufficient mosquitoes to carry out serial feeding experiments on up to 5 participants per week (60 mosquitoes per feeding event × average of 3 feeding events per participant × 5 participants = 900 per week). Sugar was removed from half of the cages on alternate days to ensure availability of sugar-starved mosquitoes on any given day.

Blood feeding

Mosquitoes were blood fed directly on the viremic participants according to a previously established procedure [9,15,32]. Briefly, two containers of 30 (15 for children <14 years of age) Ae. aegypti females from the GDLS were placed on the arms or legs of the participant for a maximum of 10 minutes in their homes. The option to carry out the feeding experiment in the U.S. Naval Medical Research Unit No. 6 (NAMRU-6) laboratory was offered as an alternative. Containers were then transported in a secure container to the NAMRU-6 laboratory for processing. Containers were placed in a −20°C freezer for about 1 minute to immobilize mosquitoes. Unfed mosquitoes were removed, and blood-engorged mosquitoes were kept in 1-pint cardboard containers with mesh tops, provided a sugar cube and sucrose solution soaked pledget, and held at 27°C and 70–80% RH for 7 to 16 days in a secure NAMRU-6 insectary. Mosquitoes were collected early (7–8 days) or late (12–16 days) relative to an expected EIP of about 10 days at 27°C [36]. The duration of extrinsic incubation was assigned randomly to containers. For most feeding events, mosquitoes were divided so that some individuals were tested early (7–8 days) and others from the same feeding event were tested later (12–16 days).

Vector competence

On the day of harvest, saliva was collected from ~20 blood-fed mosquitoes according to a previously described protocol [16] (see Fig 3 in [9]). Briefly, legs and wings were removed, and the proboscis was inserted into the end of a pipette tip containing a 1:1 solution of fetal calf serum and 30% sucrose. After 30 minutes, the solution in the pipette tip was immediately inoculated intrathoracically into 4 to 5 naïve (i.e., not previously blood-fed) recipient Ae. aegypti. After 7 days of incubation, inoculated mosquitoes that were still alive (typically 3–5) were harvested to extract total RNA. Recipient mosquitoes that shared a saliva inoculum from the same mosquito were pooled for RNA extraction. Aliquots of RNA extracted from each of the ~20 inoculated mosquito pools were combined and tested for DENV or ZIKV RNA by RT-qPCR. If the pool of RNA extracts was negative, the participant was scored not infectious to mosquitoes for that feeding event. If the pool of RNA extracts was positive, RNA from each of the ~20 inoculated mosquito pools was individually tested by RT-qPCR to determine the proportion of blood-fed mosquitoes with infectious saliva. If multiple feedings were performed on a single participant, each feeding event was considered independent of each other and pools were tested as described above.

Sample testing

Viral RNA was detected and quantified by RT-qPCR. RNA was extracted from whole blood and/or serum samples using QIAamp Viral RNA Mini Kit (Qiagen) following the manufacturer’s guidelines. The same extraction method was used for all mosquito samples except for inoculated mosquitoes, from which DENV RNA was extracted using a crude extraction method previously described [37]. Briefly, mosquito samples were placed in a vial containing a 4-mm glass bead and homogenized with a TissueLyser (Qiagen) after adding 250 μl of squash buffer (10 mM Tris pH 8.2, 1 mM EDTA, 50 mM NaCl) and 15 mg/ml of proteinase K (Qiagen). The homogenate was then heated at 56°C for 5 minutes and 98°C for 10 minutes. DENV RNA was detected and quantified using a serotype-specific TaqMan RT-qPCR assay based on a previously published method [38]. ZIKV RNA was detected and quantified using aTaqMan RT-qPCR assay targeting the envelope gene (forward primer: 5’- GATCCTACTGCTATGAGGCATC-3’; reverse primer: 5’- CCAGCCTCTGTCCACTAACGT-3’; probe: 5’- FAM-AGCCTACCTTGACAAGCAGTCAGACACTCAA-BHQ-3’) according to the following thermal profile: 50°C for 15 minutes, 95°C for 2 minutes, followed by 40 cycles of 95°C for 15 seconds and 58°C for 30 seconds. RT-qPCR assays were performed on the ABI 7500 real-time PCR platform (Applied Biosystems) using TaqMan Fast Virus 1-step RT-PCR master mix (Life Technologies) or AgPath-ID One-Step RT-PCR kit (Applied Biosystems) for DENV and Superscript III Platinum One-Step qRT-PCR kit (Invitrogen) for ZIKV. Human samples with borderline cycle threshold (Ct) values for DENV (Ct = 34–36) were confirmed positive or negative using previously extracted RNA and a nested RT-PCR protocol previously described [39]. For ZIKV, samples with borderline Ct values underwent repeat testing. The limits of detection for the DENV and ZIKV assays were 12 and 31 genome copies/μl, respectively.

Data analysis

General model considerations

Details of the model selection process are provided in S1 Text. All candidate regression models relating the probability of an individual blood-fed mosquito becoming infectious to covariates were generalized linear models or generalized linear mixed models, specifically binomial regressions with a logit link. All models were run in R 4.1.3 [40]. The potential functional forms of the relationships that were evaluated, depending on the covariate, were (a) linear, (b) binary, (c) non-parametric, (d) smooth non-linear, or (e) shape-constrained smooth non-linear. Working backwards from the most complex models, any regression that contained a shape-constrained smooth term (see Viremia section below for details) was evaluated using mosquito-level data (i.e., presence or absence of virus in saliva as determined by inoculation and subsequent testing of recipient mosquitoes) and fit using the shape-constrained additive model (scam) package [41]. In this, the response variable was thus 0 (virus-negative saliva) or 1 (virus-positive saliva). All other models were evaluated using summarized experiment-level data; i.e., the fraction of tested mosquitoes that had virus-positive saliva for a particular participant-incubation combination. As such, the response variable was equivalent to k infectious mosquitoes out of n, where k and n were specific to a particular participant-incubation combination. Any model that did not contain a shape-constrained term, but did contain a smooth non-linear term (e.g., the potential for a non-linear relationship between day of illness and transmission probability) was fit using generalized additive models with the mgcv package [42]. Models that had no smooth terms, but did consider repeated observations from the same participant, were fit using generalized linear mixed models with a random effect by individual with the lme4 package [43].

Treatment of covariates

Investigations were initiated with the simplest model and the most complex model and increased or decreased complexity as a function of model fit, parsimony, and biological feasibility, with the goal to arrive at a single model that balanced these three components. For each covariate considered, the simplest and most complex models considered are detailed below, as well as, in one case, justification for constraining the functional form to adhere more closely to biological plausibility. When possible (i.e., when comparing nested models), model comparison was done using a likelihood-ratio test. Otherwise, when appropriate, models were compared using Akaike information criterion (AIC) [44]. It should be noted that due to different response variables, models fit with scam were not directly comparable to other models in terms of AIC. In many cases, however, the same model could be re-formulated in scam to allow for direct comparison. In terms of parsimony, when two compared models had similar AIC values (within 2 units of each other [45]), the model without the shape constraint was selected over the model with one, and the linear model was selected over the non-linear one. Also in the interest of parsimony, all non-linear smooth terms were constructed with 3 interior knots and all shape-constrained smooth terms were constructed with 4 interior knots; the minimum allowed in the respective packages.

Viremia

Consistent with earlier similar studies [7,16], viremia was measured as viral RNA concentration in serum samples and log10 transformed. The simplest relationship considered between viremia and the probability of a mosquito becoming infectious was linear. A priori there is an expectation that a higher viremia would result in a higher probability of transmission; this is an assumption supported by results reported in previous literature [7,16]. As such, for the most complex relationship considered, the potential for a shape-constrained relationship between viremia and the response variable was considered, specifically a non-decreasing, monotonic smooth relationship.

Day of illness

At the time of mosquito feeding, the number of days after symptom onset ranged from 1 to 5 with more than 10 observations for each of the first 5 days post symptom onset. The simplest relationship considered was linear, while the most complex was non-linear. No a priori assumption was made about the shape of the relationship. Other researchers found a general decline in the probability of transmission with day of illness [16], but because the current study participants were enrolled earlier in their viremic period, it was unclear if the patterns previously observed would translate directly to this setting. In terms of the non-linear functional form, two approaches were considered: (1) a smooth non-linear b-spline-based term and (2) a fully non-parametric functional form where each day of illness had its own effect fit. Ostensibly, the smooth term would be the more parsimonious approach while the non-parametric functional form could allow for direct comparison between different days’ effects.

Extrinsic incubation

The duration of extrinsic incubation ranged from 7 to 16 days. A priori it was assumed that the probability of transmission would increase for longer incubation times. As such, the most complex functional form considered was a shape-constrained non-decreasing, monotonic smooth relationship. By design, experiments were either stopped early (7–8 days) or allowed to continue beyond EIP when most transmission is expected to occur naturally (12–16 days). There was no sampling on days 9, 10, or 11 post blood feeding. In addition to the complex model described above, there were two simpler models considered, as well: (1) a linear relationship for incubation time or (2) a stepped relationship with one constant effect for 7–8 days of incubation and a different constant effect for 12–16 days of incubation. Both of these simpler models use a single degree of freedom, so in the absence of fit dominance, it would be difficult to identify the most parsimonious between them.

Repeated measures

Of the 27 participants included in the analysis, 9 contributed to only one experiment; i.e., a single feeding event resulting in a single incubation-day of illness combination. Fifteen contributed to two experiments, one contributed to three, and two contributed to four. While there is potential for the influence of repeated measures on the experiment outcome (e.g., a participant who is systematically more likely to infect mosquitoes than their viremia would indicate), there are relatively low numbers of total participants and repeatedly measured participants. Due to low sample sizes and concerns around convergence and interpretability, a random effect by participant was not included. Care must be taken to not overinterpret the conclusions of our analysis as the sample size is low.

Results

We identified people with active infections by detecting viral RNA in their blood, which we refer to as viremia hereafter. A total of 54 viremic people consented to blood feed mosquitoes directly 1–4 times during their infection, which resulted in 116 mosquito feeding events. All 54 study participants were symptomatic; 96.3% were febrile. Forty-three (79.6%) participants were infected with DENV-2, 2 (3.7%) with DENV-3, and 9 (16.7%) with ZIKV. Our analysis excluded events for which viremia was detectable at enrollment but undetectable at the time of mosquito feeding, which was the case for all events involving participants with DENV-3 and ZIKV infections. Five participants (2 DENV-3 and 3 DENV-2 infections) were infectious to mosquitoes despite having undetectable viral RNA in their blood at the time of feeding. In total, our analysis was conducted on 50 feeding events involving 27 participants (44.4% female) that had detectable DENV-2 viremia at the time of feeding. Of these feeding events, 58% were on participants ≤17 years of age, 30% on participants 18–31 years of age, and 12% on participants 40–80 years of age (S1 Fig). Corresponding primary data are provided in supplementary information (S1 File) and their descriptive statistics are shown in Table 1. Variation in the number of mosquitoes tested reflects variation in the number of mosquitoes available, variation in the blood feeding rate and/or variation in the mosquito survival rate during the incubation period.

Table 1. Summary table of descriptive statistics.

Summary statistics are provided for the main variables of the final dataset analyzed.

Variable Range Median Mean Std. dev.
Participant age (years) 5–80 17 22.4 17.0
Days of illness at the time of feeding 1–5 2 2.46 1.20
Number of feeding events per participant 1–4 2 1.85 0.82
Viremia at the time of feeding (log10 scale) 2.0–9.1 5.63 5.29 2.05
Number of mosquitoes tested 1–20 18.5 16.6 4.84
Percentage of infectious mosquitoes 0–45 0 8.76 13.6

We analyzed the probability of a mosquito becoming infectious (i.e., a direct measure of vector competence) using logistic regression models. The final selected model retained a linear effect of viremia, a non-linear smooth effect of day of illness, and a stepped effect of extrinsic incubation time. While this model was not the best model in terms of AIC, no model had an AIC less than 2 units smaller and all models with smaller AIC were deemed biologically implausible (see S1 Text for details). Each term was statistically significant (Table 2). For each log10-unit increase in viremia, the odds of a mosquito being infectious were 1.38 times higher (odds ratio [OR] = 1.38, p-value <0.0001, 95% confidence interval [CI]: 1.17–1.63). Extrinsic incubation for 12 days or greater increased the odds of a mosquito being infectious by 21.3 times relative to 7 or 8 days of incubation (OR = 21.3, p-value <0.00001, 95% CI: 6.46–69.58). Fig 1 shows ORs for each day of illness against the mean estimated odds for day of illness of 1. Of particular note, the ORs for the second day of illness compared to the mean estimated effect for the first day of illness was 2.24 (95% CI: 1.56–3.21). This approach does not easily produce a p-value for this comparison, but the entire non-linear smooth model is statistically significant (p-value = 0.00565). Another model that resulted in a similar fit does allow for a direct calculation of the OR between the first and second days of illness. The model with no smooth terms, a linear effect of viremia, a non-parametric effect of day of illness, and a stepped effect of incubation time had an AIC of 139.52 (ΔAIC = 3.34). That model, which is arguably simpler even though it uses more degrees of freedom, revealed extremely similar effects of viremia and incubation time. In that model, which fit the effect of each day of illness as its own coefficient, the OR for the second day of illness compared to the first day of illness was 2.23 (p-value = 0.0062, 95% CI: 1.26–3.96). Fig 2 illustrates the fitted effects of the covariates on predicted probabilities across a wide range of potential values.

Table 2. Parameters of the final selected model.

The probability of a mosquito being infectious was analyzed using logistic regression models. The table shows the effects retained in the final selected model. Eff. df: effective degrees of freedom; Ref. df: reference degrees of freedom.

Model term Estimate Std. error z-value p-value
Intercept -7.0656 0.7934 -8.905 <2×10−16
Log viremia 0.3237 0.0831 3.895 0.000098
Incubation > 11 days 3.0541 0.6063 5.038 0.00000047
Model term Eff. df Ref. df Chi 2 p-value
Day of illness 1.91 1.99 9.775 0.00565

Fig 1. DENV transmission probability is highest on the second day of illness.

Fig 1

The odds of a mosquito being infectious for each day of illness are plotted on a log10 scale relative to the mean estimated odds for the first day of illness. Vertical bars show the 95% confidence intervals of the odds ratios. The horizontal dotted line represents an odds ratio of 1.

Fig 2. Human-to-mosquito DENV transmission depends on viremia, incubation time and day of illness.

Fig 2

DENV transmission probability was estimated by the proportion of blood-fed mosquitoes that had infectious virus in their saliva. Each circle (12–16 days of incubation) or triangle (7–8 days of incubation) represents a single mosquito feeding event and the size of the circle or triangle is proportionate to the number of mosquitoes analyzed. Lines represent the regression fits to the data. Lines and data points are color and shape coded according to the inset scale. (a) Transmission probability as a function of log10-transformed viremia. (b) Transmission probability as a function of day of illness. (c) Transmission probability as a function of extrinsic incubation time in days. (d) Log10-transformed viremia as a function of day of illness.

Discussion

In this study, we quantified human-to-mosquito DENV transmission from viremic people to determine the drivers of infectiousness to mosquitoes in a natural context. Our experimental setup allowed us to blood feed mosquitoes directly on human volunteers with mild illness during their DENV infection [9,15,32]. We measured the proportion of mosquitoes that became infectious (i.e., that had infectious virus in their saliva) and used regression analyses to identify the factors influencing this process. We confirmed that the magnitude of viremia is a significant predictor of the probability of a blood-fed mosquito becoming infectious. Consistent with earlier studies, a longer extrinsic incubation also increased transmission probability [46]. A result that is different from previous studies was that the day of illness influenced the probability of onward DENV transmission in a non-monotonic fashion with a maximum around 2 days after symptom onset. This finding challenges the previous belief that the maximum level of infectiousness to mosquitoes coincides with symptom onset [17].

Day of illness was previously found to negatively influence human-to-mosquito transmission of DENV-1 and DENV-2 from hospitalized patients enrolled 2–4 days after symptom onset [16]. For each unit increase in day of illness, the odds of a mosquito becoming infected were 0.6 times lower [16]. Our results reveal that the relationship between infectiousness and day of illness is more complex than a simple linear relationship. By using non-linear functional forms in our regression models, we found that the odds of DENV transmission on the second day of illness were 2.23 times higher than on the first day of illness. Infectiousness subsequently decreased until the fifth day of illness. One important implication of this finding is that virus transmission can be substantially reduced if mildly symptomatic DENV-infected people take protective measures against mosquito bites within the first two days of their illness. Protective measures could include personal protection (e.g., topical repellents) and/or insecticide spraying at the locations of daytime activity.

At this point, we can only speculate on the factors other than viremia that drive temporal variation in DENV infectiousness to mosquitoes. DENV-infected people experience most symptoms during their first week of illness, but there is substantial heterogeneity in the duration and reported intensity of individual symptoms [47]. Immune factors, metabolites or changes in blood concentration of viral antigens during infection could modulate mosquito infection [16,26,27,29,30]. The effect of human blood factors on vector competence could be due to their direct influence on mosquito-virus interactions or indirectly mediated by changes of the mosquito gut microbiota [48].

A limitation of our study is the small number of human participants that contributed to the analysis and the diminishing number of volunteers who participated in repeated feedings over time. We excluded 2 participants infected with DENV-3, all 9 participants infected with ZIKV, and 16 of the 43 participants with a DENV-2 infection from the final dataset because they did not have detectable viremia at the time of mosquito feeding. Due to the low number of participants retained in the analysis (n = 27), we could not account for a random effect of participant and our statistical power was limited. In addition, participants in our study did not represent the entire spectrum of disease manifestations. All of our study participants were mildly symptomatic, which is the case for the majority of DENV infections [5]. It would be helpful in the future to determine whether our conclusions extend to the entire disease spectrum, ranging from asymptomatic infections to people that experience severe dengue, and to DENV serotypes other than DENV-2.

An additional limitation of our study was to measure viremia as the concentration of viral RNA in blood, which is distinct from the concentration of infectious viral particles [49]. Variation in infectiousness to mosquitoes could reflect differences in the ratio of infectious particles over viral genome copies. Intriguingly, a few participants with undetectable viremia were infectious to mosquitoes, as was observed in our previous study [7]. This could reflect variation in viral titer between venous blood (used to measure viremia) and capillary blood (imbibed by mosquitoes) and/or between serum and whole blood.

It is notable that despite conducting feeding experiments on 9 participants infected with ZIKV, none were infectious to mosquitoes. Viremia was undetectable on the day of feeding for all ZIKV-infected participants, including four feeding experiments that took place as early as two days post symptom onset. This is consistent with the previous observation that ZIKV viremia post symptom onset can be too low to achieve a productive mosquito infection [50]. It is possible that effective human-to-mosquito ZIKV transmission primarily occurs prior to symptom onset. Additional studies are required to determine the kinetics of human-to-mosquito ZIKV transmission during the viremic period.

Our results shed new light on variation within and between different people in their contribution to onward DENV transmission. Our finding that mildly symptomatic people are most infectious to mosquitoes on the second day of their illness points to an overlooked aspect of the dynamics of DENV infectiousness to mosquitoes during the viremic period. The net contribution of an individual to DENV transmission is a function of infectiousness dynamics and the frequency of human-mosquito contacts. Exposure to mosquitoes is heterogeneous [5153] and difficult to quantify due to the unknown effect of coupled heterogeneities [54]. Human-mosquito contacts also depend on symptom severity [55], which highlights the need to relate illness with infectiousness dynamics. Detailed longitudinal information at the individual level can be used to improve surveillance and outbreak response as well as help to better inform modeling assessments of DENV transmission dynamics and the relative public health impact of different intervention tools and strategies [9].

Supporting information

S1 Fig. Demographic characteristics of 50 DENV-2 viremic feedings evaluated for infectiousness to Aedes aegypti mosquitoes.

(TIF)

S1 File. Primary data set used for analysis.

(CSV)

S1 Text. Model Selection Procedures.

Contains Figs A-B and Tables A-C. Fig A. Flow chart of model selection process. Fig B. Linear model fitting for day of illness. The plot shows the residuals of the linear fit against day of illness. Thin lines represent the 25th and 75th percentiles and solid lines represent the median. Table A. GLM with linear terms for each covariate (AIC = 163.2932). Table B. GAM with nonlinear smooth term for day of illness and linear terms otherwise (AIC = 146.0056). Eff. df: effective degrees of freedom; Ref. df: reference degrees of freedom. Table C. GLM with day of illness as a factor and linear terms otherwise (AIC = 149.6279).

(DOCX)

Acknowledgments

We thank the residents of Iquitos for their support and participation in this study. We are grateful to the Loreto Regional Health Department, including Drs. Hugo Rodriguez-Ferruci, Christian Carey, Carlos Alvarez, Hernan Silva and the Lic. Wilma Casanova Rojas, who all facilitated our work in Iquitos. W. Lorena Quiroz and Jhonny Cordova conducted dengue positive case follow-up and interviews and acknowledge the NAMRU-6 Iquitos febrile surveillance and laboratory teams in the rapid capture and diagnosis of dengue and Zika cases for direct mosquito feeding studies. We acknowledge the NAMRU-6 Virology and Emerging Infectious Disease and Command during the execution of this project. A special thanks to Gloria Talledo for her ongoing support with the preparation of protocols and reports for this project. We appreciate the commentary and advice provided by the NAMRU-6 Institutional Review Board and Research Administration Program for the duration of the study.

Data Availability

R code and data used for statistical analysis and to produce figures in the manuscript are openly available on GitHub [https://github.com/bcreiner/mosq_feeds_Iquitos] and provided as a supplementary file (S1 File), respectively.

Funding Statement

The study was primarily funded by a grant from the U.S. National Institutes of Health/National Institute of Allergy and Infectious Diseases (P01 AI098670 to TWS) with some additional salary support provided by U01AI151814 to ACM. The study was also supported by the European Union’s Horizon 2020 research and innovation programme under ZikaPLAN (734584 to LL) and the French Government’s Investissement d’Avenir program Laboratoire d’Excellence Integrative Biology of Emerging Infectious Diseases (ANR-10-LABX-62-IBEID to LL). Further support was provided by a sub contract from the Bill and Melinda Gates Foundation to the University of Notre Dame (OPP1081737 to TWS/ACM), the Defense Threat Reduction Agency, Military Infectious Disease Research Program (MIDRP, S0520_15_LI and S0572_17_LI), and the Armed Forces Health Surveillance Division, Global Emerging Infections System Branch (ProMIS ID: 20160390169, P0090_17_N6_1.1.1, P0106_18_N6_01.01, and P0143_19_N6). The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Department of the Navy, Department of Defense, nor the U.S. Government. 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 Negl Trop Dis. doi: 10.1371/journal.pntd.0011593.r001

Decision Letter 0

Elvina Viennet, Amy T Gilbert

12 May 2023

Dear Dr. Morrison,

Thank you very much for submitting your manuscript "Direct mosquito feedings on dengue and Zika virus-infected people reveal dynamics of human infectiousness" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

The reviewers and editor appreciate that the central finding of the paper, where human infectiousness to mosquitoes via bloodmeals continues to increase after (mild) dengue symptoms begin, is original and advances knowledge in the field. The authors highlight that mild dengue infections tend to be challenging to detect by surveillance and as a result their role in community transmission has been understudied and underappreciated. While the analysis and conclusions are based on a relatively limited sample size of participants eligible for and completing the bloodmeal feedings, the authors have considered appropriate statistical procedures of model selection for parameter inference, though they might consider adding a summary table of descriptive statistics, implementing alternative error distributions for modeling the data, and clarifying further the steps of their model selection using a supplemental table or image. Several suggestions were made and should be considered to improve the clarity of results shown in Figure 2. The authors adequately advise caution with the data, results, and inference, including statistical power limitations. However, reviewer concerns which must be addressed for clarity include the techniques used for mosquito husbandry and rearing, intrathoracic inoculation, and blood feeding on humans, and the potential influence of the techniques used on the results and conclusions. Lastly, the authors may consider revising the article title to more accurately reflect the focus of the results and discussion, i.e. specifically on dengue-2.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Amy T. Gilbert

Academic Editor

PLOS Neglected Tropical Diseases

Elvina Viennet

Section Editor

PLOS Neglected Tropical Diseases

***********************

The reviewers and editor appreciate that the central finding of the paper, where human infectiousness to mosquitoes via bloodmeals continues to increase after (mild) dengue symptoms begin, is original and advances knowledge in the field. The authors highlight that mild dengue infections tend to be challenging to detect by surveillance and as a result their role in community transmission has been understudied and underappreciated. While the analysis and conclusions are based on a relatively limited sample size of participants eligible for and completing the bloodmeal feedings, the authors have considered appropriate statistical procedures of model selection for parameter inference, though they might consider adding a summary table of descriptive statistics, implementing alternative error distributions for modeling the data, and clarifying further the steps of their model selection using a supplemental table or image. Several suggestions were made and should be considered to improve the clarity of results shown in Figure 2. The authors adequately advise caution with the data, results, and inference, including statistical power limitations. However, reviewer concerns which must be addressed for clarity include the techniques used for mosquito husbandry and rearing, intrathoracic inoculation, and blood feeding on humans, and the potential influence of the techniques used on the results and conclusions. Lastly, the authors may consider revising the article title to more accurately reflect the focus of the results and discussion, i.e. specifically on dengue-2.

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: The methods are sane, I just recommend making the model selection procedure a bit clearer through a graph or a table (as a supplement).

Reviewer #2: -Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

yes

-Is the study design appropriate to address the stated objectives?

yes

-Is the population clearly described and appropriate for the hypothesis being tested?

yes

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

yes

-Were correct statistical analysis used to support conclusions?

I suspect - these are outside of my expertise.

-Are there concerns about ethical or regulatory requirements being met?

no

Reviewer #3: Major issues:

Variability across data collection: there is substantial variation in the number of mosquitoes assessed in this data set, yet no explanation for this is provided. Mosquitoes rarely die off in large number during such experiments unless they are improperly treated. This may be the case here as the methods describe knock down of 5 min at -20C, which is long even for temperate mosquitoes. 30 sec at -20C is typically sufficient for Aedes aegypti strains and much longer tends to result in death. Therefore, often they are knocked down at 4C instead or -20C. Was this incorrectly provided or is this GDLS particularly cold hearty? Alternatively, were the mosquitoes not properly prepared to blood feed? For the mosquitoes that were collected post 12 days the range of collection varies from 12-16 days this is a large range that adds further complexity in analysis on an already small sample set. This adds further to the lack of confidence in the data set. Then to assess infectiousness, saliva samples are collected directly in a pipet tip and intrathoracically injected into 5 new mosquitoes seeming directly from the pipet tip. Intrathoracic injections with a pulled needle in Aedes species are difficult enough to do without killing any mosquitoes, this reviewer would like to know what ratio remain alive given it would potentially substantially skew the transmission probability here. Is day two only the highest probability because there were the most individuals available for assessment on this day and, with the highest viremia individual present on this day and counted twice as a result of the combination of the pre 12-day incubation set? Why do the authors not show the RT-qPCR results, the original viremia results, infect cell culture cells rather than this complex mosquito infection process with all the error it introduces. Or if cell culture isn’t possible then run RT-qPCR on the saliva directly from the original set of mosquitoes.

Statistical analyses: there are no statistics to demonstrate whether any of the data are reliable as the only statistics shown were identified for the purpose of being most statistically significant. There are no statistics shown for Figure 1 and what the error bars represent is not included, and day 1-3 seem nearly identical given the small numbers in the study.

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

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: The results are clear but Figure 2 could be improved in my opinion. I make some suggestions in my general comments.

Reviewer #2: -Does the analysis presented match the analysis plan?

yes

-Are the results clearly and completely presented?

yes

-Are the figures (Tables, Images) of sufficient quality for clarity?

yes

Reviewer #3: Major issues:

In the main figure of the paper, Figure 2, the legend states that a and b are only the mosquito feeding events that were incubated for between 12-16 days, which would be appropriate. However, this is not accurate. The easiest to identify is the highest viremia individuals from day two. Both extrinsic incubations are present in a, b, and d. Given 7-8 days are largely irrelevant EI time points this is inappropriate and even if it were appropriate, it doesn’t match the description provided by the authors. Overall, the inattention to detail is a cause for concern across the data provided. In addition to correcting this inaccuracy the data overall should be presented in a way that the reader can fully access. By combing four assessments per graph with little explanation for the relevance of each aspect it is difficult to assess what is significant and what is noise. Unless it’s mostly noise.

The authors bled and fed mosquitoes on at minimum 50% children. Children are not miniature adults and respond differently to viral infections when compared with adults. Given the small sample size in this manuscript it serves primarily as a steppingstone/pilot to design further directed studies based on the observations provided. The authors should provide as much detail about the data acquired as possible. Instead, the data are highly condensed and filtered.

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

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: The conclusion and discussion are well articulated and do a good job of positioning the study and pointing to possible next steps.

Reviewer #2: -Are the conclusions supported by the data presented?

yes

-Are the limitations of analysis clearly described?

yes (sample size)

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

yes, very clearly, and with strong implications for disease control

-Is public health relevance addressed?

yes

Reviewer #3: (No Response)

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

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: (No Response)

Reviewer #2: This is a great piece of work and I only have a few comments.

page 5 - starting here there are a few references to this being a field-based study, but it seems like a lot of this was done in the laboratory or insectary. It struck me as a little odd, though I don't disagree altogether.

page 8 - "As the mosquitoes emerged, females were separated into 1-pint cardboard cages containing 25 Ae. aegypti each." Were they not allowed to mate?

page 8 - in your methods under "Blood feeding" - I think the incubation periods allowed for mosquitoes after the feed could be clarified. I only understood this after getting through more of the manuscript. When you say, for example, "Experiments were either stopped early (7-8 days) or late (12-16 days)...", what are you considering an experiment? I would try something more explicit here like "~X mosquitoes were harvested on days X, X, X, and X for analysis of vector competence".

Reviewer #3: Title: no dynamics are revealed for ZIKV, or DENV3. The title is misleading. Either add a substantial amount of information about the ZIKV and DENV3 subjects/samples or focus the paper on DENV-2.

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

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: Note : please provide line numbers in the revised version of the manuscript

Introduction

The introduction is well written. As I understand it, the dataset you’re using comes from studies already published (refs 9, 15, 32). It would be helpful to more clearly identify what were the key messages of these previous studies and how the current one comes to complete the picture.

Also, can you put more emphasis on the differences and similarities between your study and the ones done in Vietnam and Cambodia (Nguyen et al. 2013, Duong et al. 2015)? Did you have a priori hypotheses on the factors that could drive differences between your results and theirs (study location, viral strains, people past exposure etc.) or were you expecting this to mostly replicate their observations and increase the robustness of the conclusions?

Lastly, an important added value of your study in my opinion is to have repeated mosquito feedings on the same individuals, which was not the case in Nguyen et al. 2013 and Duong et al. 2015 if I’m not mistaken. This is implied when you mention the “temporal dynamics of infectiousness”, or that you want to understand “variation within people”, but it could be stated even more clearly.

Methods

* Vector competence

You mention that “If the pool of RNA extracts was negative, the participant was considered to be not infectious to mosquitoes and no further mosquito testing was performed.” I guess you mean no further testing for this particular feeding on a given individual, and not possible subsequent feedings? Please precise.

* General model considerations

You mention using logistic regressions with a binomial link function. First, I think it would be more accurate to say a binomial error distribution with a logit (I assume as it’s the most common) link function. And second, have you tried comparing with a betabinomial error distribution? This would account for overdispersion, and in my experience often gives the best fit for this kind of data (improvement more tangible than including random effects).

Please precise that analyses were conducted in R before you start mentioning package names, and not after.

I acknowledge that authors intend to share their code and data through open repositories once the paper is accepted, which is great (and I intend to look at your code once it's there, as this is of interest to me).

* Viremia

You mention RNA concentration (and state in the discussion that this is a limit because it is distinct from infectious viral particles) but the initial paper (ref 9) also mentions fluorescent focus assay in its Figure 3. This would importantly give information on infectious viral load, particularly an estimation of the ratio of infectious over total viral particles, which is rare in the literature. Why was this not used here?

* Repeated measures

You explain not including a random effect by participant. But the way you phrase it, I don’t understand if you tried and it did not work/was not prefered over the model not including random effects, which I would understand, or if you simply chose not to try, which I would find odd (although as said before, I suspect trying a betabinomial model is more likely to improve your fit than random effects for this kind of experimental design).

Overall, I find the approach regarding data analysis very sane, but I’m still unsure that I understand perfectly what has been done, in terms of all model forms that were compared. As the supporting information currently only gives additional details on the results of the selection procedure, I still think it would be helpful to detail the framework of your model comparison procedure with a graph or a table (as a supplementary item as well). This would be a didactic opportunity for young (and sometimes not so young) researchers facing the same kind of analysis, and (hopefully) ensure that stepwise regression is no longer the “go-to” analysis.

Results

I am of course intrigued by your participants with no detectable viremia that did transmit to mosquitoes. Do you think this might be something to investigate, or do you attribute this to anecdotal evidence? And why did you exclude those datapoints (for DENV-2) from model fitting : did you want to constrain your probability to zero for absence of viremia? If yes, could you not have assign these participants a viremia value at the limit of detection? By the way it does not seem that the limit of detection of your assay is reported anywhere so I would add this information.

Figure 2 : y-axis text (not title) should be horizontal for better readability for all sub-figures. Same goes for the “Day of infection” legend title in a), which could then be put on top of the discrete color scale. Same with Log viremia for b-d (and it should log10 rather than log).

In the caption of the figure : “with after”, when describing (a), should be “after”

I find the figure a bit confusing to read, here are a few suggestions/comments to improve it :

For a and b : add transparency to the points and maybe change the color scales because it’s hard to associate the points with the curves of the same values, particularly for mid-range values. Maybe two types of viridis scales for a and b (https://ggplot2.tidyverse.org/reference/scale_viridis.html) ? At least for the days of infection as you only have 5 levels it should help distinguish values.

For c : why not drop the sample size and use point size to show day of illness ? Maybe it’ll get confusing with your fitted lines… But at least I don’t see why you would show the fits per viremia and not per day of illness as well : maybe a supplementary figure?

For d : the color and the y axis are redundant, why not use the color for transmission probability? Not sure sample size is really needed as well, but points shape could show the two categories of incubation time? Just a thought...

Discussion

The discussion is well structured and addresses the main limitations, contributions, and perspectives clearly.

Reviewer #2: I have just one final general comment. There will certainly be some researchers reading this that don't appreciate seeing more advanced statistical techniques. They might even gripe. I would appease this by adding in a table with some sort of summary of the raw data. The odds-ratio plot comes closest to this. They may also not be github users, so although the raw data will be available there, a summary would go a long way.

Reviewer #3: In the manuscript entitled “Direct mosquito feedings on dengue and Zika virus-infected people reveal dynamics of human infectiousness” by Louis Lambrechts and Robert C Reiner Jr. et al, the authors present data linking max transmission probability to the day of illness for dengue-2 infections. Specifically, the data suggest day two post symptom onset for dengue-2 may result in the highest transmission probability increasing from day one and falling through day five. This work involved a great deal of logistics to enroll participants and collect the samples, however the methods were previously published, so that aspect is not a new contribution to the field. All the data presented in the manuscript fit into two figures and a table, with Figure 1 and Figure 2b being the same data analyzed in different ways. While the finding that human infectiousness to mosquitoes during bloodmeals continues to increase after symptoms begin is novel, there are many issues that need to be addressed and this work seems less than what should be a minimal publishable unit.

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

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Reviewer #2: No

Reviewer #3: No

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PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0011593.r003

Decision Letter 1

Elvina Viennet

14 Aug 2023

Dear Dr. Morrison,

We are pleased to inform you that your manuscript 'Direct mosquito feedings on dengue-2 virus-infected people reveal dynamics of human infectiousness' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Elvina Viennet, PhD

Section Editor

PLOS Neglected Tropical Diseases

***********************************************************

Thank you for your thorough responses to reviewers. Please find attached few minor comments.

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: Yes to all.

Small typo, l.348 (version without tracked changes) : logit not logic

In file S.1, l.73 : "As both a linear and a non-linear…" sounds odd, I think “With either a linear or a non-linear…” would be better?

**********

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: Yes to all.

In Figure 2C, I wonder why fitted lines per viremia levels are the same for both EIP categories. Shouldn't the longer EIP had higher transmission probability, for a given viremia?

In Figure S2 : what does the thick and thin lines represent for each day?

Table S2 : consider providing more detailed column information (e.g by turning this file into an Excel with a separate sheet for column information), even though the headers are quite explicit, to avoid any confusion

**********

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: Yes to all

**********

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: In the authors' summary :

l.128 DENV-3 instead of DENV-2

l.129 one to four times? You say later that some participants were fed on four times

l.138-139 “people with mild illness are thought to contribute more to DENV transmission than more severely ill people” : this is counterintuitive at first so as you cannot cite the study by Bosch et al. Here, maybe give a bit more information to understand this statement

l.142 a better understanding

**********

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: (No Response)

**********

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0011593.r004

Acceptance letter

Elvina Viennet

24 Aug 2023

Dear Dr. Morrison,

We are delighted to inform you that your manuscript, "Direct mosquito feedings on dengue-2 virus-infected people reveal dynamics of human infectiousness," has been formally accepted for publication in PLOS Neglected Tropical Diseases.

We have now passed your article onto the PLOS Production Department who will complete the rest of the publication process. All authors will receive a confirmation email upon publication.

The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any scientific or type-setting errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript. Note: Proofs for Front Matter articles (Editorial, Viewpoint, Symposium, Review, etc...) are generated on a different schedule and may not be made available as quickly.

Soon after your final files are uploaded, the early version of your manuscript will be published online unless you opted out of this process. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers.

Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Shaden Kamhawi

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

Paul Brindley

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

Associated Data

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

    Supplementary Materials

    S1 Fig. Demographic characteristics of 50 DENV-2 viremic feedings evaluated for infectiousness to Aedes aegypti mosquitoes.

    (TIF)

    S1 File. Primary data set used for analysis.

    (CSV)

    S1 Text. Model Selection Procedures.

    Contains Figs A-B and Tables A-C. Fig A. Flow chart of model selection process. Fig B. Linear model fitting for day of illness. The plot shows the residuals of the linear fit against day of illness. Thin lines represent the 25th and 75th percentiles and solid lines represent the median. Table A. GLM with linear terms for each covariate (AIC = 163.2932). Table B. GAM with nonlinear smooth term for day of illness and linear terms otherwise (AIC = 146.0056). Eff. df: effective degrees of freedom; Ref. df: reference degrees of freedom. Table C. GLM with day of illness as a factor and linear terms otherwise (AIC = 149.6279).

    (DOCX)

    Attachment

    Submitted filename: Editorial Office Responses.docx

    Data Availability Statement

    R code and data used for statistical analysis and to produce figures in the manuscript are openly available on GitHub [https://github.com/bcreiner/mosq_feeds_Iquitos] and provided as a supplementary file (S1 File), respectively.


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