Leveraging mathematical models to support early management of an emerging disease outbreak: the case of Covid-19 and Africa
Mathematics can help face healthcare needs and challenges, being the catalyst for a profound transformation in the healthcare arena and helping improve efficiency, effectiveness, and responsiveness, as well as equity in the delivery of public health and healthcare services, by developing and facilitating current practices, and by introducing new methods of surveillance and action both at the individual (clinical medicine) and community/population (public and global health) levels. Mathematics is anticipated to uncover new links between climate, climate-related disaster exposure, and the burden of disease (especially, in terms of mental health), helping policy- and decision-makers particularly in low- and middle-income countries (LMICs), such as those belonging to the Global South to achieve SDG3 (“health and wellbeing for all”) and SDG5 (“gender equality”) . In this talk, I will focus on using mathematics to inform policies in an early-stage of an outbreak, using covid as an example. In the first part, I will present a compartmentalized epidemiological model designed to help policymakers track the early dynamics of COVID across Africa. In the second part, I will present a model designed to help policymakers to determine pre-existing country characteristics that predispose them to greater intrinsic vulnerability to COVID-19.