A serological framework to investigate acute primary and post-primary dengue cases reporting across the Philippines

Abstract

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 that categorised the reporting population as negative, historical, primary and post-primary for dengue. We validated our algorithm against WHO gold standard criteria and investigated cross-reactivity with Zika by assaying a random subset for anti-ZIKV IgM and IgG. Lastly, using our algorithm, we explored immuno-epidemiological patterns of dengue across the Philippines. Results Our modelled IgM and IgG seroprevalence thresholds were lower than kit-provided thresholds. Individuals anti-DENV PCR+ or IgM+ were classified as active dengue infections (83.1%, 6998/8425). IgG− and IgG+ active dengue infections on disease days 1 and 2 were categorised as primary and post-primary, respectively, while those on disease days 3 to 5 with IgG:IgM ratios below and above 0.45 were classified as primary and post-primary, respectively. A significant proportion of post-primary dengue infections had elevated anti-ZIKV IgG inferring previous Zika exposure. Our algorithm achieved 90.5% serological agreement with WHO standard practice. Post-primary dengue infections were more likely to be older and present with severe symptoms. Finally, we identified a spatio-temporal cluster of primary dengue case reporting in northern Luzon during 2016. Conclusions Our dengue immune status algorithm can equip surveillance operations with the means to target dengue control efforts. The algorithm accurately identified primary dengue infections who are at risk of future severe disease.

Serological Evidence of Widespread Zika Transmission across the Philippines

“…Output index values were subsequently termed ‘DENV IgM/G ELISA values’. DENV IgM and IgG seroprevalence thresholds were previously generated by the authors of [ 32 ], corresponding to 0.99 and 0.22 ELISA units (Panbio index values), respectively.…”

“…We determined individual DENV immune status according to the dengue laboratory and epidemiological data using methods previously described by the authors of [ 32 ]. Suspected dengue case reports were initially classified as active (PCR+ or IgM+) or non-active (PCR- and IgM-), as at least one of these markers should be present during an ongoing dengue infection.…”

“…Mixture modelling methods were used to determine ZIKV IgM and IgG seroprevalence as described by the authors [ 32 , 33 , 34 ] using the ‘fmm’ command in STATA (v.16). Mixture models were fit to the ZIKV IgM/IgG ELISA value data by maximum likelihood with lognormal titer distributions and two components to characterize the seronegative and seropositive subpopulations.…”

“…Catalytic models were used to determine the DENV and ZIKV force of infection (and attack rates) across the Philippines among those without active ZIKV or DENV infections as antibody levels are heavily influenced by day of infection [ 11 , 32 ]. Models fitted with maximum likelihood were used to characterize anti-ZIKV/DENV IgG age-seroprevalence and generate seroconversion rates—estimates equivalent to the force of infection.…”

Estimating the annual dengue force of infection from the age of reporting primary infections across urban centres in endemic countries

“…The serum is collected from sampled case reports for molecular and serological testing to allow spatio-temporal monitoring of dengue serotypes. Prior to this study, we utilised laboratory data from surveyed dengue patients to develop an algorithm that accurately determines individual primary or post-primary (secondary, tertiary or quaternary) immune status [ 14 ]. Despite this, it remains unknown how surveillance metrics derived from this algorithm can best be used to routinely characterise the FOI.…”