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BackgroundDespite high coverage and successes in malaria control strategies, some areas of Tanzania have indicated stagnantion or revesal of malaria burden. In malaria research, most studies are designed to assess drivers of malaria transmission focusing only on one dimension, single location while very few studies assess multiple components and their interactions at once. This article describes the protocol used to assess intrinsic and extrinsic drivers of persistent malaria transmission (hotsposts) in four regions from northwestern (Geita and Kigoma) and southern (Ruvuma and Mtwara) Tanzania.MethodsThis cross-sectional study was conducted between July and November 2017 in eight districts (two from each region). Based on the health facilities records, two villages were selected from each district. The study assessed five components individually and their linkages: socio-economic and malaria risk factors, parasitological, entomological, socio-anthropological and health system factors. Households (HHs) and household members were enumerated, socio-economic status and risk factors associated with malaria transmission were assessed. A total of 120 HHs were sampled from each village where malaria testing using rapid test and microscopy were done and blood spots on filter papers for genetic studies were collected. Heads of HHs were interviewed to capture information on knowledge, attitude, practice and beliefs towards malaria and its control. Assessment of adult mosquitoes in 25 HHs in each village and complimented with assessment of immature mosquitoes through larvae was conducted. The performance of the health system was assessed with respect to Information on availability, accessibility, affordability and quality of malaria prevention and case management services were collected from these health facilities.DiscussionThe proposed analysis plan and results from this study are expected to determine factors potentially responsible for persistence of malaria (hotspots) in the study areas. Rather than the traditional methodology of focusing on one metric, the approach proposed here triangulates observations from all five components, highlighting understanding of potential drivers while studying their complex interactions and map spatial heterogeneity. This study will provide an important framework and data which will guide future studies and malaria surveillance in Tanzania and other malaria endemic countries.

High-throughput Plasmodium genomic data is increasingly useful in assessing prevalence of clinically important mutations and malaria transmission patterns. Understanding parasite diversity is important for identification of specific human or parasite populations that can be targeted by control programs, and to monitor the spread of mutations associated with drug resistance. An up-to-date understanding of regional parasite population dynamics is also critical to monitor the impact of control efforts. However, this data is largely absent from high-burden nations in Africa, and to date, no such analysis has been conducted for malaria parasites in Tanzania country-wide. To this end, over 1,000 P. falciparum clinical isolates were collected in 2017 from 13 sites in seven administrative regions across Tanzania, and parasites were genotyped at 1,800 variable positions genome-wide using molecular inversion probes. Population structure was detectable among Tanzanian P. falciparum parasites, roughly separating parasites from the northern and southern districts and identifying genetically admixed populations in the north. Isolates from geographically close districts were more likely to be genetically related compared to parasites sampled from more distant districts. Known drug resistance mutations were seen at increased frequency in northern districts, and additional variants with undetermined significance for antimalarial resistance also varied by geography. Malaria Indicator Survey (2017) data corresponded with genetic findings, including average region-level complexity-of-infection and malaria prevalence estimates. The parasite populations identified here provide important information on extant spatial patterns of genetic diversity of Tanzanian parasites, to which future surveys of genetic relatedness can be compared.SIGNIFICANCEDocumenting dynamics of malaria parasite genomics in high-transmission settings at scale in sub-Saharan Africa is critical for policy and decision making to support ongoing malaria elimination initiatives. Using molecular inversion probes, we genotyped over 1,000 Tanzanian Plasmodium falciparum samples collected country-wide in 2017 at hundreds of variable polymorphic positions across the genome. Frequencies of known drug resistance mutations were higher in northern districts of the country compared to the south. Results also showed a distinct isolation-by-distance pattern (whereby increasing geographic distance was correlated with decreasing genetic relatedness), as well as signals of higher genetic sharing between several southern districts. These results provide, for the first time, a picture of current within-country diversity of Tanzanian P. falciparum populations.