Optimizing Covid-19 Prevention Measures In The Face Of Socio-Cultural And People's Movement Patterns in Developing Countries: Case Study of Mozambique

The coronavirus COVID-19 pandemic is the defining global health crisis of our time. Since its emergence late 2019, the vírus has spread to every continent except Antarctica, demonstrating its capacity to cross significant natural geographic barriers. As of the time of this writing (June 8th, 2020), the number of infected cases worldwide have reached 103,569 867 confirmed cases, 2 238 898 deaths and 75 193 856 recovered. Although, Africa is the least-affected region globally after Oceania in terms of the number of COVID-19 cases and deaths, since middle September cases have been increasing with steeper increases being observed since late November 2020. In Mozambique in particular steeper increases have been observed since the transition to the new year 2021 rising from below hundred cases a day to over a thousand confirmed new cases a day. Life conditions in African countries are vastly different and often fragile, with conflicting limitations of both the health care system and socio-economic conditions, posing difficult challenges for decisions about enacting and lifting interventions, and negatively influence containment as well as recording, testing and medical treatment. For example, the median age below 20, and the low rates of urbanization, could potentially lead to a lower death toll of the epidemic in African countries than elsewhere. However, having a young population implies that many infected individuals may not display symptoms and will risk infecting more people than would symptomatic individuals. Additionally, the large number of informal settlements (including residents, markets and bus stations) could accentuate this phenomenon. It is therefore urgent to develop a framework that could accurately predict the spread of the virus, accounting for the idiosyncrasies of the African context. A country-specific model will provide policy makers with a wide range of prediction scenarios, based on different actions they can take to address the pandemic. The work proposed here has the intention to contribute towards a development of tool for investigating and predicting the spatio-temporal COVID-19 pandemic activities while taking into considerations of observed trends of disease spatial spread, social behaviours, population movements patterns, migration and displacement due to war and other calamities and economic constraints by means of modelling across mathematical sciences, computing, geographic systems, social science and epidemiology. Our objective is then to use the resulting model to make prediction about the spatio-temporal spread of the disease at local and global scale and scrutinize important factors underlying such spatio-temporal patterns. Then, assess viable control strategies particularly in specific socio-cultural behaviours and economic constraints. Decision makers can use this modelling tool to determine the distribution of resources, the critical time for implementing interventions, and the severity and timing of the epidemic, thus reducing uncertainty in decision-making, leading to better management of disease and resources under specific national socio-economic profile. Expected Outputs The main results of the proposed research projected will be described in three manuscripts, highlighting the following expected knowledge outputs: - Novel relationships on the effects of significant explanatory environmental, socioeconomic, topographic, socio-cultural, and demographic variables on spatial variability of COVID-19 incidence rates established and mapped; - Impact of transnational border mobility on expanding and seeding COVID-19 infection into new geographic areas determined; - A tool for assessing relative contribution of various prevention and control strategies such as social distancing, self-quarantine, and isolation measures in high-density settings like informal settlements and co-morbidities, including population movement patterns, border closings, regional (for instance at provincial level) opening and closing strategies, re-seeding of infection, developed, tested and optimized.