Estimating probabilities of malaria importation in southern Mozambique through modelling P. falciparum genomics and mobility patterns
Arnau Pujol, Arlindo Chidimatembue, Clemente da Silva, Simone Boene, Henriques Mbeve, Pau Cisteró, Carla García-Fernández, Arnau Vañó-Boira, Dário Tembisse, José Inácio, Glória Matambisso, Fabião Luis, Nelo Ndimande, Humberto Munguambe, Lidia Nhamussua, Wilson Simone, Andrés Aranda-Díaz, Manuel García-Ulloa, Neide Canana, Maria Tusell, Júlia Montaña, Laura Fuente-Soro, Khalid Ussene Bapu, Maxwell Murphy, Bernardete Rafael, Eduard Rovira-Vallbona, Caterina Guinovart, Bryan Greenhouse, Sonia Maria Enosse, Francisco Saúte, Pedro Aide, Baltazar Candrinho, Alfredo MayorImported malaria is a critical obstacle to achieving elimination in low transmission settings, but importation classification tools combining human mobility and parasite genomics are lacking. A Bayesian model combining epidemiological, human mobility, and parasite genetic data was developed to estimate malaria importation and geographic origins of Plasmodium falciparum cases. Using microhaplotype-based genetic relatedness from 1605 samples across nine Mozambican provinces in 2022, the study focused on two low-transmission districts in the south: Magude and Matutuine. Parasites from southern Mozambique showed lower genetic relatedness to those from northern/central regions (0.021) than the national average (0.034, p<0.001), indicating limited connectivity. Overall, 42% (88/207) of infections in these districts were classified as imported, mainly originating from Inhambane province (63% [55/88]). Imported cases showed higher parasite complexity than local ones (odds ratios [OR] = 1.3). Importation rates differed markedly between districts – Matutuine (48.60%, 87/179) was far more affected than Magude (10.71%, 3/28) – highlighting the need for localised rather than uniform elimination strategies. In Matutuine, importation appears to be actively sustaining transmission, suggesting that reducing malaria burden in source regions (particularly Inhambane) and targeting travellers from central and northern Mozambique would have the greatest elimination impact.