Abstract

BackgroundAs momentum towards malaria elimination grows, strategies are being developed for scale-up in elimination settings. One prominent strategy, reactive case detection (RACD), involves screening and treating individuals living in close proximity to passively detected, or “index” cases. This study aims to use RACD to quantify Plasmodium parasitaemia in households of index cases, and identify risk factors for infection; these data could inform reactive screening approaches and identify target risk groups.MethodsThis study was conducted in the Western Cambodian province of Pailin between May 2013 and March 2014 among 440 households. Index participants/index cases (n = 270) and surrounding households (n = 110) were screened for Plasmodium infection with rapid diagnostic tests (RDT), microscopy and real-time polymerase chain reaction (PCR). Participants were interviewed to identify risk factors. A comparison group of 60 randomly-selected households was also screened, to compare infection levels of RACD and non-RACD households. In order to identify potential risk factors that would inform screening approaches and identify risk groups, multivariate logistic regression models were applied.ResultsNine infections were identified in households of index cases (RACD approach) through RDT screening of 1898 individuals (seven Plasmodium vivax, two Plasmodium falciparum); seven were afebrile. Seventeen infections were identified through PCR screening of 1596 individuals (15 P. vivax, and 22 % P. falciparum/P. vivax mixed infections). In the control group, 25 P. falciparum infections were identified through PCR screening of 237 individuals, and no P. vivax was found. Plasmodium falciparum infection was associated with fever (p = 0.013), being a member of a control household (p ≤ 0.001), having a history of malaria infection (p = 0.041), and sleeping without a mosquito net (p = 0.011). Significant predictors of P. vivax infection, as diagnosed by PCR, were fever (p = 0.058, borderline significant) and history of malaria infection (p ≤ 0.001).ConclusionThis study found that RACD identified very few secondary infections when targeting index and neighbouring households for screening. The results suggest RACD is not appropriate, where exposure to malaria occurs away from the community, and there is a high level of treatment-seeking from the private sector. Piloting RACD in a range of transmission settings would help to identify the ideal environment for feasible and effective reactive screening methods.

Highlights

  • As momentum towards malaria elimination grows, strategies are being developed for scale-up in elimination settings

  • polymerase chain reaction (PCR) was not conducted on index cases. 96 % of all households were contacted within 3 days of notification

  • Infections identified by reactive case detection (RACD) Out of 1898 people screened by rapid diagnostic tests (RDT) using RACD, nine were positive (0.5 %)

Read more

Summary

Introduction

As momentum towards malaria elimination grows, strategies are being developed for scale-up in elimination settings. Reactive case detection (RACD), involves screening and treating indi‐ viduals living in close proximity to passively detected, or “index” cases. This study aims to use RACD to quantify Plasmodium parasitaemia in households of index cases, and identify risk factors for infection; these data could inform reactive screening approaches and identify target risk groups. As of 2014, 34 of the 99 malariaendemic countries have adopted strategies to become malaria-free within the two decades [4, 5] Their strategies largely involve shifting the focus from early diagnosis and treatment of febrile malaria cases, to active surveillance to facilitate early detection and treatment of every individual infection, including those who are afebrile [6]. Reactive case detection (RACD) is one strategy commonly described or promoted for scale-up in elimination settings. Case-finding through RACD essentially takes advantage of the spatial and temporal clustering of malaria infections associated with transmission hotspots [18,19,20]

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call