Integrating mobility, travel survey, and malaria case data to understand drivers of malaria importation to Zanzibar, 2022–2023

Abstract

Background: Zanzibar has achieved historic reductions in malaria incidence, but high connectivity to mainland Tanzania and imported cases remain a challenge to “last mile” malaria elimination. Methods: To understand factors driving malaria importation, prospective surveys were administered to patients at 94 health facilities across Zanzibar’s main island, Unguja, from May 2022 to December 2023, and to travellers at the Zanzibar-bound ferry terminal in Dar es Salaam from August to December 2024. In addition, digital mobility data—Meta colocation and movement distribution—were analysed to examine movement patterns between Unguja and mainland Tanzania. These data were integrated with rainfall data to explore the seasonality of human movement and travel-associated malaria risk. Results: Of 3,875 total malaria cases presenting to health facilities in Unguja, 1,172 reported travel to mainland Tanzania within the past 30 days (283/511 (55%) in 2022, 889/3,348 (27%) in 2023). Among these, travel to Tanga (20%), Dar es Salaam (20%), and Morogoro (15%) were most common. Children and females had higher odds of having malaria associated with travel to the mainland (aOR 3.2, 95% CI: 2.2–4.8 and aOR 1.5, 95% CI: 1.3–1.8, respectively, compared to those without mainland travel), while nightwatchmen and students with malaria were more likely to report travel within Zanzibar. Twenty-eight percent of travel-associated malaria cases reported primary residence on the mainland. However, Zanzibari residents who reported travel to mainland regions with high or moderate malaria risk during the dry season made up the highest proportion of travel-related malaria cases (n = 309, 32%). Meta movement distribution data shows that long-distance travel off Unguja decreases during the rainy seasons. In addition, imported cases correlated with rainfall at their mainland destination, rather than rainfall in Zanzibar. With different biases, data from both Meta colocation and ferry surveys approximated the proportional makeup of at-risk travel from different geographies relatively well. In particular, Meta colocation data highlighted travel between Tanga and Unguja, likely via private boats, not captured in the ferry data. Conclusions: Movement flows and seasonal rainfall patterns drive imported malaria in predictable ways that can be harnessed to target high-risk travellers for intervention.