Abstract
Serology has become an increasingly important tool for the surveillance of a wide range of infectious diseases. It has been particularly useful to monitor malaria transmission in elimination settings where existing metrics such as parasite prevalence and incidence of clinical cases are less sensitive. Seroconversion rates, based on antibody prevalence to Plasmodium falciparum asexual blood-stage antigens, provide estimates of transmission intensity that correlate with entomological inoculation rates but lack precision in settings where seroprevalence is still high. Here we present a new and widely applicable method, based on cross-sectional data on individual antibody levels. We evaluate its use as a sero-surveillance tool in a Tanzanian setting with declining malaria prevalence. We find that the newly developed mathematical models produce more precise estimates of transmission patterns, are robust in high transmission settings and when sample sizes are small, and provide a powerful tool for serological evaluation of malaria transmission intensity.
Highlights
Serology has become an increasingly important tool for the surveillance of a wide range of infectious diseases
Seroprevalence and levels of antibodies to P. falciparum antigens increased with age at both surveys, except for MSP-119, MSP-3_3D7 and MSP-3_k1 in the 2010 cross-section where levels were similar across age groups
Data on antibody levels were approximately log-normally distributed for all antigens and highly correlated between the two allelic variants of apical membrane antigen 1 (AMA-1) and merozoite surface protein 3 (MSP-3), while less correlated for merozoite surface protein 2 (MSP-2)
Summary
Serology has become an increasingly important tool for the surveillance of a wide range of infectious diseases. Seroconversion rates, based on antibody prevalence to Plasmodium falciparum asexual blood-stage antigens, provide estimates of transmission intensity that correlate with entomological inoculation rates but lack precision in settings where seroprevalence is still high. Existing methods for serological evaluation of malaria transmission have largely been based on cross-sectional data on antibody prevalence and on estimation of seroconversion rates (SCR) using serocatalytic models as shown by Drakeley et al.[15]. SCR based estimates have been extended to evaluate temporal changes[21,22,23] and provide robust information about medium and long-term trends of transmission intensity, they are insensitive to changes in high transmission settings and to smaller and more short-term trends due to the quick acquisition of antibody responses and the long half-life of seropositivity to many blood-stage antigens[15,24,25]. SCR based estimates could potentially be further improved by the application of a model that makes use of the data on individual antibody levels by assuming that antibody levels increase as a function of age, and that the rate at which they are boosted by exposure can be used as a marker of transmission intensity
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