Deciphering Residual Malaria Mechanisms in the Peruvian Amazon to Inform Novel and Effective Control Strategies

About This Grant

Project Summary The Peru Amazon region of Loreto (capital, Iquitos) accounts for 95% of all malaria in Peru, and ranks as contributing to ~25% of all malaria cases in the Americas. Peru has repeatedly launched elimination plans, most recently in 2022, based on case-finding strategies, field-deployable molecular diagnosis, and vector control measures conceived within the previously funded, NIAID-supported, Amazonian ICEMR network. Two contexts remain a challenge to achieve malaria elimination goals: (i) residual malaria transmission with sustained hypoendemicity despite the use of currently available interventions, and (ii) focal hyperendemic transmission in hard-to-reach Indigenous populations. This proposal focuses on residual urban and close-by and remote riverine transmission areas with increasing proportions of asymptomatic cases, regardless of age. Malaria transmission in these remote areas remains high and difficult to control, and the past two years have seen important rises in malaria cases. We first aim to characterize a wide range of sociodemographic, behavioral, and environmental factors that, in addition to human genetics, contribute to individual risk of malaria (re)infection and disease in the Amazon. We will estimate the relative contribution of genetic and nongenetic (potentially modifiable) factors to individual malaria risk variation and identify risk profiles in populations from residual malaria settings in Peru. Next, we will apply network analysis to analyze the interconnectedness of malaria parasite carriers between remote and more proximal sites, which we hypothesize leads to continued malaria transmission with residual malaria settings as an important source. In addition, we will track malaria transmission trends and identify hotspots in remote indigenous populations in Peru by applying field-deployable molecular diagnosis and modeling sequential antibody measurements. In summary, we will advance knowledge on individual malaria risk profiles and the impact of targeted interventions in residual malaria contexts. We will also characterize malaria transmission in hard-to-reach areas where the malaria burden is poorly understood and mitigated. Collectively, this study will make significant contributions by integrating and translating diverse data and analytic frameworks into actionable knowledge and evidence to support tailored malaria elimination efforts in Peru, elsewhere in South America, and similar contexts in the world beyond, including the protection of United States domestic and military interests.