Malaria is preventable and treatable – but it is still deadly. In 2015, there were 214 million cases of malaria and an estimated 438,000 deaths. Nearly nine in ten cases occur in Sub-Saharan African, and the direct and indirect costs of this burden are high.
This is the eighth in our series of job market posts this year
The Global Fund has disbursed nearly $28.4 billion in the last decade to reduce the disease burden from malaria, TB and HIV (Global Fund 2016). However, travelers can reverse the progress from campaigns that have decreased infectious disease prevalence (Cohen 2012 et al, Lu et al 2014), or can rapidly spread emerging diseases such as Ebola and Zika (Tam et al 2016, Bogoch et al 2016). While policymakers have largely targeted environmental drivers of malaria, this research provides evidence that human movement can play an important role in spreading disease in areas where incidence has been reduced. Given that migration has numerous economic and social benefits, policymakers face important trade-offs in designing policies to reduce travel-linked malaria cases. This paper provides a useful framework for identifying high-risk populations in order to reduce malaria incidence with minimal interference to movement patterns.
We know malaria is a big problem and we know fake drugs are a big problem. What do you get when you put them together? Bad news. A recent paper by Martina Bjorkman-Nyqvist, Jakob Svensson and David Yanagizawa-Drott (ungated version here) shows how bad this problem is in Uganda, and provides an innovative way to deal with it.
David has started a discussion that I find intrinsically interesting and one that well-designed impact evaluations can help clarify: why don’t more people adopt low-cost efficacious health technologies? We may be able to think of examples in our own lives – i.e. “why don’t I take vitamins more regularly?” or “why, if diabetic, don’t I self-test my blood sugar more frequently?” These same questions also resonate for large-scale health programs in many settings.
Diseases like malaria, diarrhea and intestinal worms plague hundreds of millions of people in the developing world. A major puzzle for development researchers and practitioners is why the poor do not purchase available prevention technologies that could reduce the burden of these diseases. While much of the recent literature has focused on price elasticities of demand and behavioral explanations, another potential explanation is that liquidity constraints prevent the poor from undertaking profitable health investments.