Using health facility-based serological surveillance to predict receptive areas at risk of malaria outbreaks in elimination areas

• Main Authors: Henry Surendra, Supargiyono, Riris A. Ahmad, Rizqiani A. Kusumasari, Theodola B. Rahayujati, Siska Y. Damayanti, Kevin K. A. Tetteh, Chetan Chitnis, Gillian Stresman, Jackie Cook, Chris Drakeley
• Format: Article
• Language: English
• Published: BMC 2020-01-01
• Series: BMC Medicine
• Subjects: Serology; Surveillance; Mapping; Malaria; Elimination
• Online Access: https://doi.org/10.1186/s12916-019-1482-7

Abstract Background In order to improve malaria burden estimates in low transmission settings, more sensitive tools and efficient sampling strategies are required. This study evaluated the use of serological measures from repeated health facility-based cross-sectional surveys to investigate Plasmodium falciparum and Plasmodium vivax transmission dynamics in an area nearing elimination in Indonesia. Methods Quarterly surveys were conducted in eight public health facilities in Kulon Progo District, Indonesia, from May 2017 to April 2018. Demographic data were collected from all clinic patients and their companions, with household coordinates collected using participatory mapping methods. In addition to standard microscopy tests, bead-based serological assays were performed on finger-prick bloodspot samples from 9453 people. Seroconversion rates (SCR, i.e. the proportion of people in the population who are expected to seroconvert per year) were estimated by fitting a simple reversible catalytic model to seroprevalence data. Mixed effects logistic regression was used to examine factors associated with malaria exposure, and spatial analysis was performed to identify areas with clustering of high antibody responses. Results Parasite prevalence by microscopy was extremely low (0.06% (95% confidence interval 0.03–0.14, n = 6) and 0 for P. vivax and P. falciparum, respectively). However, spatial analysis of P. vivax antibody responses identified high-risk areas that were subsequently the site of a P. vivax outbreak in August 2017 (62 cases detected through passive and reactive detection systems). These areas overlapped with P. falciparum high-risk areas and were detected in each survey. General low transmission was confirmed by the SCR estimated from a pool of the four surveys in people aged 15 years old and under (0.020 (95% confidence interval 0.017–0.024) and 0.005 (95% confidence interval 0.003–0.008) for P. vivax and P. falciparum, respectively). The SCR estimates in those over 15 years old were 0.066 (95% confidence interval 0.041–0.105) and 0.032 (95% confidence interval 0.015–0.069) for P. vivax and P. falciparum, respectively. Conclusions These findings demonstrate the potential use of health facility-based serological surveillance to better identify and target areas still receptive to malaria in an elimination setting. Further implementation research is needed to enable integration of these methods with existing surveillance systems.