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  • 1.
    Armando, Chaibo Jose
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health.
    Rocklöv, Joacim
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health. Heidelberg Institute of Global Health and Interdisciplinary Centre for Scientific Computing, Heidelberg University, Heidelberg, Germany.
    Sidat, Mohsin
    Faculty of Medicine, Eduardo Mondlane University, Maputo, Mozambique.
    Tozan, Yesim
    School of Global Public Health, New York University, NY, New York, United States.
    Mavume, Alberto Francisco
    Faculty of Science, Eduardo Mondlane University, Maputo, Mozambique.
    Bunker, Aditi
    Center for Climate, Health, and the Global Environment, Harvard T.H. Chan School of Public Health, MA, Boston, United States; Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany.
    Sewe, Maquins Odhiambo
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health. Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany.
    Climate variability, socio-economic conditions and vulnerability to malaria infections in Mozambique 2016–2018: a spatial temporal analysis2023In: Frontiers In Public Health, ISSN 2296-2565, Vol. 11, article id 1162535Article in journal (Refereed)
    Abstract [en]

    Background: Temperature, precipitation, relative humidity (RH), and Normalized Different Vegetation Index (NDVI), influence malaria transmission dynamics. However, an understanding of interactions between socioeconomic indicators, environmental factors and malaria incidence can help design interventions to alleviate the high burden of malaria infections on vulnerable populations. Our study thus aimed to investigate the socioeconomic and climatological factors influencing spatial and temporal variability of malaria infections in Mozambique.

    Methods: We used monthly malaria cases from 2016 to 2018 at the district level. We developed an hierarchical spatial–temporal model in a Bayesian framework. Monthly malaria cases were assumed to follow a negative binomial distribution. We used integrated nested Laplace approximation (INLA) in R for Bayesian inference and distributed lag nonlinear modeling (DLNM) framework to explore exposure-response relationships between climate variables and risk of malaria infection in Mozambique, while adjusting for socioeconomic factors.

    Results: A total of 19,948,295 malaria cases were reported between 2016 and 2018 in Mozambique. Malaria risk increased with higher monthly mean temperatures between 20 and 29°C, at mean temperature of 25°C, the risk of malaria was 3.45 times higher (RR 3.45 [95%CI: 2.37–5.03]). Malaria risk was greatest for NDVI above 0.22. The risk of malaria was 1.34 times higher (1.34 [1.01–1.79]) at monthly RH of 55%. Malaria risk reduced by 26.1%, for total monthly precipitation of 480 mm (0.739 [95%CI: 0.61–0.90]) at lag 2 months, while for lower total monthly precipitation of 10 mm, the risk of malaria was 1.87 times higher (1.87 [1.30–2.69]). After adjusting for climate variables, having lower level of education significantly increased malaria risk (1.034 [1.014–1.054]) and having electricity (0.979 [0.967–0.992]) and sharing toilet facilities (0.957 [0.924–0.991]) significantly reduced malaria risk.

    Conclusion: Our current study identified lag patterns and association between climate variables and malaria incidence in Mozambique. Extremes in climate variables were associated with an increased risk of malaria transmission, peaks in transmission were varied. Our findings provide insights for designing early warning, prevention, and control strategies to minimize seasonal malaria surges and associated infections in Mozambique a region where Malaria causes substantial burden from illness and deaths.

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  • 2.
    Armando, Chaibo Jose
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health. School of Atmospheric Science, Nanjing University of Information Science and Technology (NUIST), Nanjing, China.
    Yu, Zhao
    School of Atmospheric Science, Nanjing University of Information Science and Technology (NUIST), Nanjing, China.
    Mavume, Alberto F.
    Eduardo Mondlane University, P.O. Box 257, Maputo, Mozambique.
    Ongoma, Victor
    International Water Research Institute, Mohammed VI Polytechnic University, Lot 660, Hay Moulay Rachid, Ben Guerir, Morocco.
    Nyongesa, Aston Matwayi
    School of Atmospheric Science, Nanjing University of Information Science and Technology (NUIST), Nanjing, China; Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
    Formation and track of tropical cyclones Eline (2000) and Bonita (1996)2021In: Meteorology and atmospheric physics (Print), ISSN 0177-7971, E-ISSN 1436-5065, Vol. 133, no 6, p. 1691-1706Article in journal (Refereed)
    Abstract [en]

    The occurrence of extreme rainfall events over mainland Mozambique associated with tropical cyclones (TC) Eline and Bonita is studied. Bonita caused catastrophic flooding in the central and some parts of northern Mozambique, thus forming the basis of the present study. Results show that the intensity of these TCs was maintained by the easterly wind from the Mascarene High. The northeasterly monsoon wind and northwesterlies from the Benguela current converged at the center of the TC, acting as a moisture source. The rainfall related to the two TCs befell in three stages and its magnitude attenuated progressively from the coastal region toward inland, concurring with the degeneration of the TCs. In stage one, for Eline, rainfall mainly concentrated in Tete, Manica, Niassa, North of Gaza provinces, the coastal Nampula, Zambezia, Sofala and Inhambane provinces. During Bonita’s inner-core circulation landfall, the northern and few parts of central Bonita were directly inundated. In the second stage, for Eline, the center of concentration of rainfall was in the central and southern parts of Mozambique. The mechanisms, including warm-air advection, vertical wind shear, could have contributed at the same time to the lifting vital for the generation of the storm during the second stage. The information herein is essential for future forecasting and monitoring of TC over the Indian Ocean. The findings form a good reference in the understanding of the recent cyclones, Kenneth and Idai that were destructive over Mozambique.

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