Dengue viremia kinetics and effects on platelet count and clinical outcomes: An analysis of 2340 patients from Vietnam

Background: Viremia is a critical factor in understanding the pathogenesis of dengue infection, but limited data exist on viremia kinetics. This study aimed to investigate the kinetics of viremia and its effects on subsequent platelet count, severe dengue, and plasma leakage. Methods: We pooled data from three studies conducted in Vietnam between 2000 and 2016, involving 2340 dengue patients with daily viremia measurements and platelet counts after symptom onset. Viremia kinetics were assessed using a random effects model that accounted for left-censored data. The effects of viremia on subsequent platelet count and clinical outcomes were examined using a landmark approach with a random effects model and logistic regression model with generalized estimating equations, respectively. The rate of viremia decline was derived from the model of viremia kinetics. Its effect on the clinical outcomes was assessed by logistic regression models. Results: Viremia levels rapidly decreased following symptom onset, with variations observed depending on the infecting serotype. DENV-1 exhibited the highest mean viremia levels during the first 5–6 days, while DENV-4 demonstrated the shortest clearance time. Higher viremia levels were associated with decreased subsequent platelet counts from day 6 onwards. Elevated viremia levels on each illness day increased the risk of developing severe dengue and plasma leakage. However, the effect size decreased with later illness days. A more rapid decline in viremia is associated with a reduced risk of the clinical outcomes. Conclusions: This study provides comprehensive insights into viremia kinetics and its effect on subsequent platelet count and clinical outcomes in dengue patients. Our findings underscore the importance of measuring viremia levels during the early febrile phase for dengue studies and support the use of viremia kinetics as outcome for phase-2 dengue therapeutic trials. Funding: Wellcome Trust and European Union Seventh Framework Programme.


Introduction
Dengue is the most common arboviral infection worldwide and is found mainly in tropical and subtropical areas.The disease has been a growing threat for decades, and in 2019 the World Health Organization (WHO) ranked it among the top 10 threats to global health (World Health Organization, 2009;World Health Organization, 2020).It is estimated that 105 million people are infected by dengue annually, of whom half develop symptoms (Cattarino et al., 2020).Although most infections are asymptomatic or self-limiting, the small proportion of patients who develop complications can still overwhelm health systems in dengue-endemic countries during seasonal epidemics.Climate change, increasing global travel, and urbanization all serve to amplify the distribution of Aedes aegypti, the main vector responsible for dengue transmission (Whitehorn and Yacoub, 2019;Yacoub et al., 2011).Although dengue has been known for centuries, specific treatment is still to be found, and the two licensed vaccines are of limited benefit (Kariyawasam et al., 2023;Redoni et al., 2020).
Exploring the variation in viremia levels could help improve our understanding of disease pathogenesis and potentially facilitate assessment of new vaccines and treatments for dengue.For example, knowing the natural kinetics of dengue viremia may help in selection of patient groups or timing of antiviral use in therapeutic intervention trials.Dengue viremia kinetics has been investigated in several studies (Ben-Shachar et al., 2016;Clapham et al., 2016;Clapham et al., 2014;Duyen et al., 2011;Matangkasombut et al., 2020;Nguyet et al., 2013;Simmons et al., 2007a;Tricou et al., 2011).The main findings are: (1) viremia rapidly decreases after symptom onset; (2) dengue virus (DENV)-1 infection gives higher viremia level than DENV-2 and DENV-3; and (3) primary infection gives higher viremia than secondary infection in DENV-1.However, these studies had limited sample sizes, particularly for DENV-4 serotype, and did not provide a full account of viremia kinetics.Three studies constructed mechanistic mathematical models and focused on investigating the role of the host immune response in controlling viremia (Ben-Shachar et al., 2016;Clapham et al., 2016;Clapham et al., 2014).Another study assessed viremia in infants aged under 18 months (Simmons et al., 2007a); the findings cannot be generalized to older children or adults.Others focused on peak viremia level after symptom onset, time to viral clearance and/or the probability of detecting virus on each illness day (Duyen et al., 2011;Matangkasombut et al., 2020;Nguyet et al., 2013;Tricou et al., 2011).In most analyses, viremia levels below the limit of detection were simply set as zero, which may not be appropriate.
Quantifying the effect of viremia level on clinical outcomes is important to understand the mechanisms leading to severe disease.We and others have previously found that higher viremia levels are associated with more severe dengue (Duyen et al., 2011;Endy et al., 2004;Morsy et al., 2020;Tang et al., 2010;Tricou et al., 2011;Vaughn et al., 2000;Vuong et al., 2021), but the effect size was not strong (Vuong et al., 2021).However, all analyses were based on a single viremia value per individual.Investigating how individual viremia levels at different times after symptom onset affect the risk of severe outcome potentially provides new insights into pathogenic mechanisms.Another important question is whether a more rapid decline in viremia is associated with a lower risk of more severe clinical outcomes.One study has shown a slower rate of viral clearance being associated with more severe outcomes (Wang et al., 2006), while others have shown no association (Fox et al., 2011;Vaughn et al., 2000).This lack of conclusive evidence underscores the need for further investigation.In addition, the relationship between viremia kinetics and platelet count kinetics -an important hematological indicator -has yet to be investigated.
This study aims to improve our understanding of viremia kinetics, how it is associated with patient characteristics and virus serotype, and how it impacts disease severity, using a dataset derived from several thousand individuals with symptomatic dengue.First, we fitted a model for individual viremia kinetics that treats values below the detection limit as censored data, and assessed whether viremia kinetics differed by age, sex, serotype, or immune status.Second, we modeled platelet count kinetics and explored dependence on viremia level.We investigated the potential existence of a lagged effect of viremia, by analyzing platelet counts measured on and following the day of viremia assessment.Third, we modeled the effect of viremia levels measured at different days after symptom onset and the effect of the rate of viremia decline on development of two clinical outcomes, plasma leakage and severe dengue.

Study population
We used data from three prospective observational studies performed as part of the longstanding collaboration between the Oxford University Clinical Research Unit (OUCRU) and the Hospital for Tropical Diseases (HTD) in Ho Chi Minh City, Vietnam.Protocol synopses for the three studies are presented in Appendix 1.Briefly, studies A and B simultaneously ran from 2000 to 2009 and enrolled children aged between 5 and 15 years.Study A included children with a febrile illness presenting to community outpatient clinics, while study B included children admitted to HTD with a febrile illness suspected to be dengue.Some patients from study A were subsequently enrolled in study B after admission to hospital.Study C ran from 2011 to 2016 and enrolled adults and children presenting with possible dengue within 3 days of fever onset (IDAMS study, NCT01550016) (Jaenisch et al., 2016).Clinical evaluation and blood sampling were performed daily for all three studies.All studies were approved by the Oxford Tropical Research Ethics Committee and the Institutional Ethics Committee.We identified 3527 laboratory-confirmed dengue patients.Among them, 2340 had relevant data on viremia kinetics and were included in this analysis (Figure 1).Details of dengue diagnostics are in Appendix 2.

Plasma viremia measurement, dengue diagnostics, and clinical endpoints (details in Appendix 2)
Plasma viremia levels were measured by reverse transcription polymerase chain reaction (RT-PCR), which was an internally controlled, serotype-specific, real-time, two-step assay in studies A and B (Simmons et al., 2007b), and a one-step procedure using a validated assay in study C (Hue et al., 2011).There was no formal validation of the detection limit for viremia for the two-step PCR used in studies A and B; we set it at 1000 copies/ml.In the one-step PCR used in study C, the detection limit was 300 copies/ml for DENV-1 and DENV-3, 60 copies/ml for DENV-2, and 600 copies/ml for DENV-4 (Hue et al., 2011).
Patients were classified into probable primary (i.e., the first) or probable secondary (i.e., a second or subsequent) infection based on IgG results on paired samples.A probable primary infection was defined by two negative/equivocal IgG results on separate samples taken at least 2 days apart within the first 10 days of symptom onset, with at least one sample during the convalescent phase (days 6-10).A probable secondary infection was defined by at least one positive IgG result during the first 10 days.Cases without time-appropriate IgG results were classified as indeterminate.
For the clinical endpoints we selected severe dengue and plasma leakage.The definitions are based on the WHO 2009guidelines (World Health Organization, 2009) and standard endpoint definitions for dengue trials (Tomashek et al., 2018).Severe dengue was defined as severe plasma leakage, severe bleeding, and/or severe organ impairment.Plasma leakage included moderate and severe leakage.

Statistical analysis (details in Appendix 3)
In Appendix 3-figure 1 we show a directed acyclic graph (DAG) to display assumptions about the causal relationships between variables over illness day.Illness day is the number of days after symptom onset, where day 1 is the day of symptom onset.Potential confounders that needed to be corrected for were age, sex, DENV serotype, and primary/secondary immune status.In all analyses, we used a log-10 transformation for viremia levels.
We modeled viremia kinetics over time and explored dependence on age, sex, serotype, immune status, and PCR method using a linear mixed-effects regression model, allowing for left-censored values in the outcome variable.In the fixed effect, we allowed for interactions between serotype and immune status, and between illness day and all other covariates.Nonlinear trends by age and illness day were investigated using splines with three and four knots, respectively.We included a random effect with an intercept and splines for illness day with four knots to model the intra-person correlation.Due to the presence of a left-skewed distribution in log-10 viremia (Appendix 4-figure 1), a sensitivity analysis was conducted using the 10th-root transformation.
Platelet counts were transformed using a fourth-root transformation since the distribution was right-skewed (Appendix 4-figure 2).The effect of viremia on subsequent platelet count was investigated using the landmark approach (van Houwelingen and Putter, 2011).For each illness day from 1 to 7, a landmark dataset was created, which included viremia on that day, platelet count from that day to day 10, and the time-fixed variables (age, sex, serotype, immune status, and PCR method).For the supermodel that combined all landmark datasets, we used a linear mixed-effects model including viremia, age, sex, serotype, immune status, PCR method, illness day and landmark.In the fixed effect, we also included four-way interactions between viremia, serotype, PCR method and (1) and immune status, (2) illness day, and (3) landmark day.Splines with three knots were used to allow for nonlinear trends in log-10 viremia, age, illness day, and landmark day.We included a random effect with an intercept by the combination of individuals and landmark, and splines for illness day with three knots.
The effect of viremia on the clinical endpoints was investigated using a logistic regression model using the landmark approach (van Houwelingen and Putter, 2011).For each illness day from 1 to 7, a landmark dataset was created, which included viremia on that day, occurrence of the endpoint on or after that day, and the time-fixed variables similar to above.All individuals who had already experienced the relevant endpoint before that day were excluded.We fitted a logistic regression model for each landmark dataset and then fitted a supermodel that combined all the datasets.For the supermodel we used generalized estimating equations to account for repeated inclusion of individuals at multiple landmarks.We included viremia, age, sex, serotype, immune status, study, and landmark day, and allowed for the four-way interaction between viremia, serotype, immune status, and landmark day, and two-way interactions between viremia and all other covariates.Splines were used to allow for nonlinear trends in log-10 viremia (three knots), age (three knots), and landmark (three knots).Since plasma leakage had missing data, we performed an analysis with imputed data using multiple imputation by chained equations.The imputation was done in our previous study (Vuong et al., 2021).
To calculate the rate of viremia decline for each patient, we assumed a linear decline in log-10 viremia over time.We modified our viremia kinetics model by using a linear term for illness day rather than the original nonlinear terms, both in the fixed and in the random effect.For each patient, we then calculated fitted values using this model.The rate of viremia decline was defined as the daily difference in log-10 viremia.We assessed the impact of the decline rate on the clinical endpoints using logistic regression models.We did not use the landmark approach for this analysis since the decline rate was assumed to be constant over time.Covariates included the decline rate, serotype, immune status, and PCR method.Due to limited number of severe dengue cases, its model did not include any interaction terms.The plasma leakage model incorporated interactions between the decline rate and all other covariates.
In the analyses for platelet count and clinical outcomes, undetectable viremia levels were set as the specific detection limits, and a binary dummy variable (yes/no) was created to indicate whether the viremia value was undetectable.Since the individual spline terms are hard to interpret and the large dataset makes most differences statistically significant, results are primarily reported using plots of predicted values.All analyses were done using the statistical software R version 4.1.0(R Core Team, 2021) with 'MCMCglmm' (Hadfield, 2010), 'lme4' (Bates et al., 2015), 'geepack' (Halekoh et al., 2006), and 'rms' (Harrell, 2021) packages for the models.

Results
Baseline characteristics and outcomes are summarized in Table 1.Three quarters of the participants were children, and male sex predominated (60%).Most patients (85%) were enrolled on illness day 2 or 3.All four serotypes were included, but DENV-1 was the most prevalent (54%).Most infections (69%) were classified as probable secondary infection, while in 11% immune status could not be determined.There were 353 patients (15%) with plasma leakage and 65 patients (3%) with severe dengue.In Appendix 4-table 1, we summarize plasma leakage and severe dengue by serotype and immune status.DENV-2 had the highest proportion of these two outcomes.Patients with probable secondary infection were more likely to experience these outcomes than those with probable primary infection or indeterminate immune status, regardless of the infecting serotype.

Viremia kinetics and the relationship with clinical characteristics
Individual viremia trajectories are shown in Figure 2. Most individuals had a decreasing trend from day 1 or 2 onwards.However, values higher than the baseline value were observed up to day 7 (Appendix 4-figure 3).The decreasing trend was consistent across all combinations of serotype and immune status (Figure 2).

Effect of viremia on subsequent platelet count
Figure 4 shows the mean platelet counts by viremia levels based on the supermodel for the onestep PCR method.There was minimal impact of viremia on days 1-5 platelet count.However, higher The dashed lines indicate the detection limits, which are 300 copies/ml for DENV-1 and DENV-3, 60 copies/ml for DENV-2, and 600 copies/ml for DENV-4 in the one-step PCR cohort, and 1000 copies/ml in the two-step PCR cohort.Fifty-seven measured values that are lower than 1000 copies/ml in the two-step PCR cohort are considered as below the detection limit.Values below the detection limit are visually represented as 1/10 of the corresponding detection limit (on the original scale).DENV, dengue virus; PCR, polymerase chain reaction.
viremia levels gave decreased subsequent platelet counts from day 6 onwards, for all serotypes.The strength of this effect increased with later illness day and was more pronounced in DENV-1 and DENV-2 compared to DENV-3 and DENV-4.All covariates had low p values (Appendix 6-table 1).The effect of viremia on subsequent platelet count remained consistent across subgroups of immune status, sex, and age.In the two-step PCR cohort, the effect of viremia on platelet count was less pronounced compared to the one-step PCR cohort, although the overall trends were similar (Appendix 6-figure 1).

Effect of viremia on clinical outcomes
Higher viremia levels increased the risk of severe dengue and plasma leakage for each of the serotypes (Figure 5).The effect of viremia on both endpoints decreased with later landmark day of viremia measurement, particularly for severe dengue (Appendix 7-table 1).However, these trends were not clear in the results obtained from the simple logistic regression models at each landmark time point (Appendix 7-figure 1).This trend remained consistent across subgroups of sex, age, and study (Appendix 7-figure 2).Furthermore, the results were consistent between the analyses with and without imputation (Appendix 7-figure 3).The supermodel revealed that older individuals had a relatively lower risk of developing severe dengue, but the trend was not significant.Males exhibited a slightly higher risk of severe dengue compared to females.The effect of serotype on the two endpoints was dependent on immune status.Individuals with probable secondary infection had a higher risk of experiencing both endpoints compared to those with probable primary infection (Appendix 7-figure 4).From the model of viremia kinetics with a linear trend of illness day, the individual rate of viremia decline ranged from 0.58 to 2.01 log-10 copies/ml/day, with a median of 1.39 log-10 copies/ml/day.The logistic regression model demonstrated that a faster decline in viremia reduced the risk of severe dengue and plasma leakage (Figure 6).The effect on plasma leakage was stronger in the probable secondary infection group (Appendix 7-table 2).

Discussion
In this study, we conducted a comprehensive analysis using a large dataset of 2340 viremic dengue patients to examine viremia kinetics from first presentation, its association with various virus and patient characteristics, and its impact on subsequent platelet count and disease severity.As others have described, we found that plasma viremia declines rapidly following the onset of symptoms, with the kinetics primarily influenced by the specific infecting serotype.Higher viremia levels were associated with a decrease in subsequent platelet count from day 6 onwards.Elevated viremia levels were found to increase the risk of developing severe dengue and plasma leakage, with the effect becoming weaker at later days.The effects of viremia on platelet count and clinical outcomes did not differ much by different subgroups of serotype, immune status, age, and sex.Moreover, a faster decline in viremia was associated with a reduced risk of the more severe clinical outcomes.
There is a limited number of published papers that studied the individual trajectory of dengue viremia.Most used data from Vietnam (Ben-Shachar et al., 2016;Clapham et al., 2016;Clapham et al., 2014;Duyen et al., 2011;Nguyet et al., 2013;Simmons et al., 2007a;Tricou et al., 2011), while one was from Thailand (Matangkasombut et al., 2020).Our study has provided further evidence supporting previous findings.We confirmed that (1) viremia rapidly decreases following the onset of symptoms, (2) DENV-1 exhibits higher viremia levels compared to DENV-2 and DENV-3, and (3) primary infection is associated with higher and more prolonged detectable viremia than secondary infection in DENV-1, while this pattern was not consistent across other serotypes.We have added viremia kinetics of DENV-4, and showed that viremia levels declined more rapidly than the other serotypes.Furthermore, our study demonstrated that the new PCR test has the ability to detect plasma viremia for a longer period compared to the older test.This may be attributed to the lower detection limits of the new test.Explaining the differences in viremia kinetics between serotypes remains challenging, as the molecular factors of the virus that influence plasma viremia levels are still unknown.It is also important to note that our study focused on the time since symptom onset rather than the time since infection.We cannot rule out that some of the observed differences are explained by a difference in time from infection to symptom onset.
Our study suggests that higher viremia levels on any day before day 6 are associated with reduced platelet count on days 6-8, typically corresponding to the nadir of platelet count.Additionally, it is possible that viremia in the initial 4 days after symptom onset could affect platelet count with a delay of 3-4 days.The direct involvement of the dengue virus in triggering platelet activation and apoptosis can contribute to the development of thrombocytopenia.Thrombocytopenia in dengue infection is thought to occur through two mechanisms: bone marrow suppression, which reduces thrombopoiesis, and increased peripheral platelet clearance (Quirino-Teixeira et al., 2022).Various processes contribute to these mechanisms, including platelet-leukocyte and platelet-endothelial cell interactions, phagocytosis, complement-mediated lysis, aggregation, and clot formation.Additionally, several host immune response factors are involved in platelet activation (Balakrishna Pillai et al., 2022).In our analysis, we considered interactions between viremia level and both serotype and immune status.Interestingly, we observed that the effect of viremia level on subsequent platelet count did not differ much by serotype and immune status.
Higher plasma viremia levels increase the risk of worse clinical outcomes, as demonstrated in our previous study that only utilized viremia at enrollment during the febrile phase (Vuong et al., 2021).The diminishing impact of viremia on the two endpoints on later illness days may be attributed to the heightened immune responses that are likely triggered by higher viremia levels, and the resulting complex interplay between these factors that underlies progression to severe dengue.The effects of viremia, age, serotype, immune status, and illness day on the clinical endpoints in this study are consistent with those observed in the previous study.The similarity between these two analyses, along with the weaker effect of viremia at later days, suggests that viremia levels around the time of symptom onset could serve as a reliable predictor of dengue severity.It suggests that the early febrile phase, specifically illness days 1-3, is the critical period of measuring viremia levels in clinical practice and dengue studies.Secondary infection remains a substantial risk factor for more severe outcomes, while viremia kinetics are not influenced much by immune status.These findings suggest that immune status and viremia may be independent predictors of clinical outcomes, following distinct pathways.
The landmark approach enabled us to investigate the effect of viremia on platelet count and the clinical endpoints at each illness day, ranging from days 1 to 7, while ensuring that the viremia measurements preceded the occurrence of the outcomes.The supermodel allows for investigation of trends of the effects, while gaining power because we assume the effects of some fixed factors (e.g., age and sex) to remain constant over time.There might be other potential confounders such as host genetic and immune response factors, but these data were not available.Moreover, we assumed that the relation between viremia level and platelet count was one-way: viremia level affects platelet count.Whether platelet count affects viremia is unknown.
A notable strength of our study is the utilization of a large pooled dataset, which allowed for a flexible modeling approach to investigate the influence of age, sex, serotype, and immune status, as well as their interactions and nonlinear trends.The use of a model that accounts for left-censored data was needed for capturing the distribution of viremia levels, considering the significant proportion of undetectable values observed.
The study has several limitations.First, the study only included patients from Vietnam, which may restrict the generalizability of the findings to other countries and regions.Second, our study assessed viral RNA in the plasma, including both viable and non-viable viral particles, which could potentially lead to an overestimation of the infectious viral particles in the blood.Lastly, data during the incubation period were unavailable as patients are typically not diagnosed with dengue until symptom onset.Therefore, the trajectory of viremia from the time of infection onwards could not be demonstrated, and symptom onset was used as the reference point instead of infection.This could potentially lead to an inaccurate interpretation of the results if the incubation period is influenced by the same factors that we included in our analyses.For example, in cases of secondary infection, the immune response is stronger and quicker than in primary infection.This might lead to a shorter duration between infection and symptom onset, as well as faster viral clearance.
In conclusion, our findings reveal that viremia levels exhibit a rapid decline shortly after symptom onset, becoming undetectable after approximately 1 week in the majority of patients.Viremia kinetics display variations depending on the infecting serotype.Higher viremia levels are associated with a subsequent reduction in platelet count on illness days 6-8, and an increased risk of experiencing more severe clinical outcomes.Viremia serves as an important predictor of dengue outcomes, independent of the host immune status.However, when considering our previous analysis that involved single early viremia measurements, the addition of daily viremia measurements may not enhance the prediction of worse clinical outcomes.Thus, the measurement of viremia levels during the early febrile phase is an important marker for clinical practice and dengue-related research.Moreover, a faster decline in viremia was found to be associated with a reduced risk of more severe clinical outcomes, suggesting that viremia kinetics could be a good surrogate endpoint for phase-2 dengue therapeutic trials.Study subjects: previously healthy children aged 5-15 years, presenting to hospital outpatient clinics or to one of several local health centers in Ho Chi Minh City on day 1 or 2 of a non-specific febrile illness.Children were followed daily in the community.In the event of admission to hospital, patients continued to be followed either on the dengue ward or on PICU of the Hospital for Tropical Diseases in HCMC, according to clinical severity.
Study setting: parents/guardians of eligible patients were informed about the study and gave consent.After enrollment baseline blood and urine samples were obtained.Patients were then asked to return each day for 7 days or until full recovery, and then at 1-2 weeks and 1-2 months for follow-up.The study nurse assessed each child in the clinic every day, obtained daily blood and urine samples, and requested a medical opinion if there were any concerns about the child or the daily blood results.Two trained study doctors supervised the nurses in the clinics and followed any patients admitted to the hospital.Management in the clinic or referral for hospital admission was at the discretion of the clinic doctors, in consultation with the dengue study doctors.
Data collection: demographic and clinical data were collected on each patient at study entry using a standard case report form.Clinical progress was documented each day specifically focusing on the occurrence of bleeding manifestations or signs of vascular leakage.There was no systematic data collection regarding organ dysfunction as the clinicians felt that these problems were rare in this age group, and no biochemistry (e.g., liver/renal function) test results were documented in the research files.
Laboratory confirmation of dengue: either positive reverse transcription polymerase chain reaction (RT-PCR) or seroconversion by ELISA (IgM or IgG or both).Testing for dengue non-structural protein 1 (NS1) was performed occasionally but was not part of the original study protocol. Publications:

Study B Title: Mild Dengue Study
Study objectives: this study was part of a larger programme of work aiming to (1) estimate the burden of pediatric dengue disease in HCMC, (2) explore the mechanisms of the endothelial dysfunction associated with dengue by detailed study of well characterized patients throughout the evolution of the disease, and (3) investigate whether commonly available laboratory parameters measured during the febrile period can be used to predict subsequent disease severity.Study period: 2000-2009 Study subjects: children 5-15 years presenting to the Hospital for Tropical Diseases in HCMC with a febrile illness consistent with possible dengue, who required hospital admission to the paediatric dengue ward, NOT those admitted to HDU/ICU.Only children admitted from home were included (i.e., not transfers from other hospitals).
Study setting: parents/guardians of eligible patients were informed about the study and gave consent.All patients were followed daily until discharge with simple study notes and a daily full blood count (plus any other tests clinically indicated), and treated according to individual diagnoses.On the day of study enrolment all patients had a plasma sample obtained for research investigations.On the 6th illness day a second plasma sample was obtained.At discharge the notes were reviewed and each child was assigned a final diagnosis and clinical disease category, using carefully defined severity criteria for vascular leak and bleeding.The patients were asked to return for follow-up at 1 month, and again at 2 months if there were any ongoing concerns.
Data collection: demographic and clinical data were collected on each patient at study entry using a standard case report form.Clinical progress was documented each day specifically focusing on the occurrence of bleeding manifestations or signs of vascular leakage.There was no systematic data collection regarding organ dysfunction as the clinicians felt that these problems were rare in this age group, and no biochemistry (e.g., liver/renal function) test results were documented in the research files.
Laboratory confirmation of dengue: either positive RT-PCR or seroconversion by ELISA (IgM or IgG or both).NS1 testing was not performed. Publications: Study C Title: IDAMS -observational study in early dengue ( ClinicalTrials.gov Identifier: NCT01550016) Study objectives: to improve diagnosis and clinical management of dengue through approaches designed (1) to differentiate between dengue and other common febrile illness within 72 hr of fever onset, and ( 2) among patients with dengue to identify markers predictive of the likelihood of evolving to a more severe disease course.Study period: 2011-2016 Study subjects: both adults and children (≥5 years) were eligible for enrolment.This was a prospective multi-center observational study that enrolled approximately 7500 patients presenting with a febrile illness consistent with possible dengue to outpatient health facilities in urban centers in eight countries across Asia and Latin America.Following appropriate informed consent, subjects presenting at one of the designated sites with fever for ≤72 hr without localizing features, i.e., consistent with a possible diagnosis of dengue, were enrolled.
Study setting: following enrolment, clinical history and examination findings were recorded in the case report form and a 3-to 5-ml (age-dependent) research blood sample was obtained, together with appropriate samples to measure a range of haematological and biochemical parameters in line with local laboratory capacity.Patients were then reviewed daily in the OPD until fully recovered and afebrile for 24 hr, or for up to 6 days from enrolment.A full blood count was carried out each day, and on the last acute illness visit (within approximately 24 hr of defervescence) a second sample for a biochemical profile was obtained together with a sample for serology.All patients were then asked to attend a final follow-up visit around days 10-14 of illness, at least 1 week from the last visit during the acute illness.All management decisions throughout the acute illness were at the discretion of the clinic physicians.Any patient requiring hospital admission continued to be followed daily using a similar but more detailed case report form (CRF), with the indication(s) for admission documented, and all management interventions recorded together with the physician's rationale for these interventions.Data collection: a structured clinical questionnaire was completed upon enrolment and then once daily for up to 6 days for all patients in the study.This CRF included detailed clinical signs and symptoms, as well as all standard laboratory results including liver and renal function.
Laboratory confirmation of dengue: any case with virological evidence of dengue as shown by a positive RT-PCR assay or NS1 ELISA test, was defined as having laboratory-confirmed dengue. Publications: 1

Severe organ impairment
Assessments were not systematic.For patients investigated on the basis of the attending clinician's concerns the following definitions were applied.
Severe liver involvement: An acute clinical syndrome consistent with acute hepatitis, with new onset jaundice or coagulopathy (INR ≥1.5) or encephalopathy.
Severe neurological involvement: Any new onset acute neurological signs or symptoms, except occurrence of a single simple febrile convulsion with full recovery within 30 min.
Severe renal involvement: Increase in creatinine to more than 1.5 times the upper limit of normal for age, without existing kidney disease.
Note that the criteria used for classifying dengue severity are derived from the World Health Organization guidelines (World Health Organization, 2009) and standard endpoint definitions for dengue trials (Tomashek et al., 2018).These criteria have been adjusted to align with the actual circumstances and the data accessible for the studies included in this analysis.log-10 viremia, age, and landmark day.We included the interactions between viremia with all other covariates (age, sex, and study) and the four-way interaction between log-10 viremia with serotype, immune status, and landmark day.
Due to the limited number of severe dengue cases (65 in total), the interactions allowed in the models for severe dengue and plasma leakage differed: For severe dengue, we did not include any interactions between the binary variable describing detectable viremia with other covariates.Log-10 viremia and landmark day were specified as a linear trend in the interactions.
For plasma leakage, we additionally included the interactions between the binary variable describing detectable viremia with all other covariates (age [as a linear trend], sex, serotype, immune status, study, and landmark illness day [as a linear trend]).In the interactions between log-10 viremia and others, log-10 viremia was specified as a linear trend, whereas age and landmark day was specified with splines (similar to in the main terms).
The formula of the supermodels was as follows: : splines of landmark day with three knots at 2, 4, and 6 • LM [linear] : linear trend of landmark day Some missing data were present for plasma leakage and immune status (i.e., the indeterminate immune status).In the complete-case analysis, individuals with missing plasma leakage were excluded, and immune status was analyzed with three groups, including indeterminate status.In the imputed data analysis, we used results from the imputation performed in the previous analysis of the effect of viremia in the early febrile phase on clinical outcomes (Vuong et al., 2021).Logistic regression was the imputation model for immune status and plasma leakage.All available baseline data were included in the imputation model, including study, age, gender, weight, enrolment date, illness day at enrolment, serotype, immune status, hematocrit and platelet count at enrolment, and the outcomes (hospitalization along with its characteristics [illness day when hospitalized and length of hospital stay], plasma leakage, and severe dengue).Twenty imputed datasets were generated, and 25 cycles per dataset were performed.Rubin's rules were applied to pool estimates from the logistic regression models over the imputed datasets.

Figure 1 .
Figure 1.Flowchart illustrating the process of patient selection.@ Among 385 laboratory-confirmed dengue patients in study A, 31 individuals were later included in study B upon hospitalization.Of these, nine had viremia measurements available in both studies and were consequently analysed in study A. The remaining 22 lacked viremia data in study A but had measurements in study B, leading to their inclusion in study B in the analysis.# Although study B spanned from 2000 to 2009, daily viremia levels were only measured between 2006 and 2008.$ In study C, one study site in Vietnam did not have daily viremia measurements.Overall, a random sample of 2340 from 3527 laboratory-confirmed dengue patients had data on viremia kinetics.PCR, polymerase chain reaction.

Figure 2 .
Figure 2. Individual trajectories of measured viremia levels for (A) the one-step PCR cohort and (B) the two-step PCR cohort.The dots represent the measured viremia levels and are connected by lines for each individual patient.The dashed lines indicate the detection limits, which are 300 copies/ml for DENV-1 and DENV-3, 60 copies/ml for DENV-2, and 600 copies/ml for DENV-4 in the one-step PCR cohort, and 1000 copies/ml in the two-step PCR cohort.Fifty-seven measured values that are lower than 1000 copies/ml in the two-step PCR cohort are considered as below the detection limit.Values below the detection limit are visually represented as 1/10 of the corresponding detection limit (on the original scale).DENV, dengue virus; PCR, polymerase chain reaction.

Figure 3 .
Figure 3. Fitted trends in mean viremia levels for (A) serotype, (B) immune status, (C) sex, and (D) age.The colored lines represent the estimated mean viremia levels, and the colored shaded regions represent the corresponding 95% credible intervals.The horizontal lines represent the detection limits (D1, D2, D3, and D4 denote DENV-1, DENV-2, DENV-3, and DENV-4, respectively).Dashed lines indicate fitted viremia levels that are below the detection limit.Viremia levels are shown for age of 10 years, male sex, serotype DENV-1, probable secondary infection, and using the one-step PCR.DENV, dengue virus; PCR, polymerase chain reaction.

Figure 5 .
Figure 5. Probability of occurrence of (A) severe dengue and (B) plasma leakage, according to viremia levels -results from the supermodel.The colored lines or dots represent the probability of the endpoints.The colored shaded regions and whiskers indicate the corresponding 95% confidence intervals.Each column represents the effect of viremia on a specific day.No fitted trends are made for DENV-4 in LM day 7 since viremia was undetectable in almost all DENV-4 cases from day 7 onwards.Note that due to the limited number of severe dengue in primary infections (only 1 case in DENV-1) and plasma leakage in primary DENV-4 (see Appendix 4-table1), the estimated probability of having these outcomes is nearly zero across all viremia levels within these subgroups.The probabilities are shown for age of 10 years, male sex, probable secondary infection, and from Study C. DENV, dengue virus, LM, landmark; PCR, polymerase chain reaction; U, under the limit of detection.

Figure 6 .
Figure 6.Probability of occurrence of (A) severe dengue and (B) plasma leakage, according to the rate of decline in viremia.The colored lines represent the probability of the endpoints.The colored shaded regions indicate the corresponding 95% confidence intervals.

1 Give
individuals at each stage of study-eg numbers potentially eligible, examined for eligibility, confirmed eligible, included in the study, completing follow-up, and analysed Pages 5-6, Figure study participants (eg demographic, clinical, social) and information on exposures and potential confounders Pages 7-8,

Table 1 .
Baseline characteristics and clinical outcomes.
Vuong et al. eLife 2024;13:RP92606.DOI: https:// doi.org/ 10. 7554/ eLife.92606 14 of 45 member of the Roche Advisory Board on Severe Dengue and (b) as a member of the Data Monitoring and Adjudication Committees for the Takeda dengue vaccine trials, both outside the remit of the submitted work.The other authors declare that no competing interests exist.The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.For the purpose of Open Access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.

Table 1
Indicate number of participants with missing data for each variable of interestPages 7-8, Table1Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based Page 14 *Give information separately for exposed and unexposed groups.Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting.The STROBE checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http:// www.plosmedicine.org/,Annals of Internal Medicine at http://www.annals.org/,and Epidemiology at http://www.epidem.com/).Information on the STROBE Initiative is available at http://www.strobe-statement.org.