Papers by Mary Anne Joy Reyes
PLOS Neglected Tropical Diseases
Background Characterising dengue virus (DENV) infection history at the point of care is challengi... more Background Characterising dengue virus (DENV) infection history at the point of care is challenging as it relies on intensive laboratory techniques. We investigated how combining different rapid diagnostic tests (RDTs) can be used to accurately determine the primary and post-primary DENV immune status of reporting patients during diagnosis. Methods and findings Serum from cross-sectional surveys of acute suspected dengue patients in Indonesia (N:200) and Vietnam (N: 1,217) were assayed using dengue laboratory assays and RDTs. Using logistic regression modelling, we determined the probability of being DENV NS1, IgM and IgG RDT positive according to corresponding laboratory viremia, IgM and IgG ELISA metrics. Laboratory test thresholds for RDT positivity/negativity were calculated using Youden’s J index and were utilized to estimate the RDT outcomes in patients from the Philippines, where only data for viremia, IgM and IgG were available (N:28,326). Lastly, the probabilities of being ...
Additional file 9. Mean annual age of cases with dengue warning signs by city. The average annual... more Additional file 9. Mean annual age of cases with dengue warning signs by city. The average annual age of reported dengue cases with warning signs among study-participating cities between 2014 and 2018.
Additional file 8. Mean annual primary dengue age by city. The average annual age of reported pri... more Additional file 8. Mean annual primary dengue age by city. The average annual age of reported primary dengue infections among study-participating cities between 2014 and 2018.
Additional file 5. Reported dengue immune status by year and city. The reported primary/post-prim... more Additional file 5. Reported dengue immune status by year and city. The reported primary/post-primary immune status of reporting active dengue infection by year and city across the Philippines between 2014 and 2018. Vertical bars: 95%CI.
Additional file 4. City-aggregated dengue incidence estimates.
Additional file 2. Population demographics of study-participating cities.
Additional file 3. Methods used to determine primary and post-primary dengue immune status.
Additional file 1. Serum samples collected from dengue case reports. The number of serum samples ... more Additional file 1. Serum samples collected from dengue case reports. The number of serum samples collected from surveyed dengue case reports who reported and resided in 13 cities across the Philippines between 2014 & 2018.
Additional file 9. Scatter plots of anti-DENV and anti-ZIKV IgM (blue) and IgG (red) among those ... more Additional file 9. Scatter plots of anti-DENV and anti-ZIKV IgM (blue) and IgG (red) among those categorised as primary and post-primary dengue according to A2. Horizontal dash: seroprevalence thresholds according to Euroimmune™ specifications (1.1 antibody ratios).
Additional file 2. Study population demographics. Demographic characteristics of study population... more Additional file 2. Study population demographics. Demographic characteristics of study population with complete data (Final dataset), those missing serological /molecular data and those missing symptom data.
Additional file 6. Anti-DENV IgG:IgM mixture model component selection. Model fit comparison of 2... more Additional file 6. Anti-DENV IgG:IgM mixture model component selection. Model fit comparison of 2-component, compared to 1-component, mixture models characterising disease day stratified IgG:IgM ratio distributions among active DENV cases. AIC: Akaike information criterion. Bold: statistically favoured model component.
Additional file 7. Validation of A2 compared to the WHO gold standard method of determining dengu... more Additional file 7. Validation of A2 compared to the WHO gold standard method of determining dengue immune status. WHO immune classification: dengue immune status according to WHO guidelines. Blue: serological agreement. Red: Serological disagreement.
BMC Medicine, 2021
Background Stratifying dengue risk within endemic countries is crucial for allocating limited con... more Background Stratifying dengue risk within endemic countries is crucial for allocating limited control interventions. Current methods of monitoring dengue transmission intensity rely on potentially inaccurate incidence estimates. We investigated whether incidence or alternate metrics obtained from standard, or laboratory, surveillance operations represent accurate surrogate indicators of the burden of dengue and can be used to monitor the force of infection (FOI) across urban centres. Methods Among those who reported and resided in 13 cities across the Philippines, we collected epidemiological data from all dengue case reports between 2014 and 2017 (N 80,043) and additional laboratory data from a cross-section of sampled case reports (N 11,906) between 2014 and 2018. At the city level, we estimated the aggregated annual FOI from age-accumulated IgG among the non-dengue reporting population using catalytic modelling. We compared city-aggregated FOI estimates to aggregated incidence an...
BMC Medicine, 2020
Background In dengue-endemic countries, targeting limited control interventions to populations at... more Background In dengue-endemic countries, targeting limited control interventions to populations at risk of severe disease could enable increased efficiency. Individuals who have had their first (primary) dengue infection are at risk of developing more severe secondary disease, thus could be targeted for disease prevention. Currently, there is no reliable algorithm for determining primary and post-primary (infection with more than one flavivirus) status from a single serum sample. In this study, we developed and validated an immune status algorithm using single acute serum samples from reporting patients and investigated dengue immuno-epidemiological patterns across the Philippines. Methods During 2015/2016, a cross-sectional sample of 10,137 dengue case reports provided serum for molecular (anti-DENV PCR) and serological (anti-DENV IgM/G capture ELISA) assay. Using mixture modelling, we re-assessed IgM/G seroprevalence and estimated functional, disease day-specific, IgG:IgM ratios th...
Additional file 6. FOI catalytic model comparison. Catalytic model fit comparison of simple versu... more Additional file 6. FOI catalytic model comparison. Catalytic model fit comparison of simple versus reversible catalytic model used to estimate FOI among sampled cities. AIC: Akaike information criterion. Lower AIC (bold) indicates superior model fit.
Additional file 7. The city and study period aggregated association between the average annual FO... more Additional file 7. The city and study period aggregated association between the average annual FOI, according to simple catalytic models, and surveillance metrics. A: crude incidence. B: Under five incidence. C: Under 10 incidence. D: Mean age of case reports. E: Mean age of case reports with warning signs. F: Mean age of case reports with severe dengue. G: Mean age of active infections. H: Mean age of primary dengue infections. I: Mean age of post-primary dengue infections. ρ: Pearson's R. A-F: Data from passive surveillance G-I: Data from laboratory surveillance. Red dash: predicted FOI according to regression models for metrics with statistically significant associations with FOI (ρ, p-value>0.05).
Additional file 10. Annual city Attack rates by city according to the mean age of suspected dengu... more Additional file 10. Annual city Attack rates by city according to the mean age of suspected dengue cases with warning signs.
Additional file 3. Anti-DENV IgM mixture model component selection. Model fit comparison of a 3-c... more Additional file 3. Anti-DENV IgM mixture model component selection. Model fit comparison of a 3-component, compared to a 1-component, mixture model characterising the anti-DENV IgM titre distribution of the study population. AIC: Akaike information criterion.
Viruses, 2021
Zika virus (ZIKV) exposure across flavivirus-endemic countries, including the Philippines, remain... more Zika virus (ZIKV) exposure across flavivirus-endemic countries, including the Philippines, remains largely unknown despite sporadic case reporting and environmental suitability for transmission. Using laboratory surveillance data from 2016, 997 serum samples were randomly selected from suspected dengue (DENV) case reports across the Philippines and assayed for serological markers of short-term (IgM) and long-term (IgG) ZIKV exposure. Using mixture models, we re-evaluated ZIKV IgM/G seroprevalence thresholds and used catalytic models to quantify the force of infection (attack rate, AR) from age-accumulated ZIKV exposure. While we observed extensive ZIKV/DENV IgG cross-reactivity, not all individuals with active DENV presented with elevated ZIKV IgG, and a proportion of dengue-negative cases (DENV IgG-) were ZIKV IgG-positive (14.3%, 9/63). We identified evidence of long-term, yet not short-term, ZIKV exposure across Philippine regions (ZIKV IgG+: 31.5%, 314/997) which was geographica...
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Papers by Mary Anne Joy Reyes