Background: Great strides have been made in combating malaria, however, the indicators in sub Saharan Africa still do not show promise for elimination in the near future as malaria infections still result in high morbidity and mortality among children. The abundance of the malaria-transmitting mosquito vectors in these regions are driven by climate suitability. In order to achieve malaria elimination by 2030, strengthening of surveillance systems have been advocated. Based on malaria surveillance and climate monitoring, forecasting models may be developed for early warnings. Therefore, in this thesis, we strived to illustrate the use malaria surveillance and climate data for policy and decision making by assessing the association between weather variability (from ground and remote sensing sources) and malaria mortality, and by building malaria admission forecasting models. We further propose an economic framework for integrating forecasts into operational surveillance system for evidence based decisionmaking and resource allocation.  Methods: The studies were based in Asembo, Gem and Karemo areas of the KEMRI/CDC Health and Demographic Surveillance System in Western Kenya. Lagged association of rainfall and temperature with malaria mortality was modeled using general additive models, while distributed lag non-linear models were used to explore relationship between remote sensing variables, land surface temperature(LST), normalized difference vegetation index(NDVI) and rainfall on weekly malaria mortality. General additive models, with and without boosting, were used to develop malaria admissions forecasting models for lead times one to three months. We developed a framework for incorporating forecast output into economic evaluation of response strategies at different lead times including uncertainties. The forecast output could either be an alert based on a threshold, or absolute predicted cases. In both situations, interventions at each lead time could be evaluated by the derived net benefit function and uncertainty incorporated by simulation.  Results: We found that the environmental factors correlated with malaria mortality with varying latencies. In the first paper, where we used ground weather data, the effect of mean temperature was significant from lag of 9 weeks, with risks higher for mean temperatures above 250C. The effect of cumulative precipitation was delayed and began from 5 weeks. Weekly total rainfall of more than 120 mm resulted in increased risk for mortality. In the second paper, using remotely sensed data, the effect of precipitation was consistent in the three areas, with increasing effect with weekly total rainfall of over 40 mm, and then declined at 80 mm of weekly rainfall. NDVI below 0.4 increased the risk of malaria mortality, while day LST above 350C increased the risk of malaria mortality with shorter lags for high LST weeks. The lag effect of precipitation was more delayed for precipitation values below 20 mm starting at week 5 while shorter lag effect for higher precipitation weeks. The effect of higher NDVI values above 0.4 were more delayed and protective while shorter lag effect for NDVI below 0.4. For all the lead times, in the malaria admissions forecasting modelling in the third paper, the boosted regression models provided better prediction accuracy. The economic framework in the fourth paper presented a probability function of the net benefit of response measures, where the best response at particular lead time corresponded to the one with the highest probability, and absolute value, of a net benefit surplus.  Conclusion: We have shown that lagged relationship between environmental variables and malaria health outcomes follow the expected biological mechanism, where presentation of cases follow the onset of specific weather conditions and climate variability. This relationship guided the development of predictive models showcased with the malaria admissions model. Further, we developed an economic framework connecting the forecasts to response measures in situations with considerable uncertainties. Thus, the thesis work has contributed to several important components of early warning systems including risk assessment; utilizing surveillance data for prediction; and a method to identifying cost-effective response strategies. We recommend economic evaluation becomes standard in implementation of early warning system to guide long-term sustainability of such health protection programs.

This thesis explores and analyses the manifold relations between migration and health, what I call the migration-health nexus, in the contemporary Nicaraguan context. The study is based on fieldwork in León and Cuatro Santos and a mixed-methods approach combining qualitative in-depth interviews and quantitative survey data. In the thesis health is “traced” within the migration process; i.e. in places of origin, during travel, at the destination and after return, including the situation and consequences for both migrants and family members to migrants (“left-behinds”). The study shows that migration-health relations in Nicaragua are connected to broader economic, social and political factors and to the country’s historical experiences of colonization, neo-colonization and structural adjustments. Contemporary Nicaraguan migrations are primarily related to the strategies of making a living and the struggle for a better life (i.e. a practice of mobile livelihoods). In the study setting health concerns were both indirectly embedded in people’s mobile livelihoods, as well as directly influencing decisions to move or to stay, and migration involved both advantages and disadvantages for health. Through migration, women could see an end to physical violence and sexual abuse. Internal migrants could improve their access to health care and medicine. Vulnerabilities related to the unpredictable nature conditions could be avoided through moving. And, through the money made from migrant work people’s everyday lives and health could be improved, in terms of better nutrition, housing, and access to education, health care and medicine. However, remittances do not necessarily lead to development, as they are used to compensate for the lacking public sector in Nicaragua. Under these circumstances, I argue that the Nicaraguan population is not guaranteed their social rights of citizenship. I also argue that the negative aspects surrounding migration must be taken into account when discussing the development potentials of migration and remittances. Both internal and international migrants in this study experienced stress while moving to a new place. International migrants had difficulties accessing health care in the destination, particularly those lacking documentation. The separation within families due to migration often caused emotional pain. Family members left behind did not rate their physical health as good as often as non-migrant families. The vulnerability, stress experiences and sufferings of migrants and left-behinds varied, however. I therefore conclude that social differences (in terms of e.g. gender, class, skin colour, and legal immigration status) are key for the enactment of the migration-health nexus, and that an interplay of individual, social and structural factors influence the outcome.