Malaria morbidity and mortality in Ebola-affected countries caused by decreased health-care capacity, and the potential effect of mitigation strategies: a modelling analysis

Abstract

Summary Background The ongoing Ebola epidemic in parts of west Africa largely overwhelmed health-care systems in 2014, making adequate care for malaria impossible and threatening the gains in malaria control achieved over the past decade. We quantified this additional indirect burden of Ebola virus disease. Methods We estimated the number of cases and deaths from malaria in Guinea, Liberia, and Sierra Leone from Demographic and Health Surveys data for malaria prevalence and coverage of malaria interventions before the Ebola outbreak. We then removed the effect of treatment and hospital care to estimate additional cases and deaths from malaria caused by reduced health-care capacity and potential disruption of delivery of insecticide-treated bednets. We modelled the potential effect of emergency mass drug administration in affected areas on malaria cases and health-care demand. Findings If malaria care ceased as a result of the Ebola epidemic, untreated cases of malaria would have increased by 45% (95% credible interval 43–49) in Guinea, 88% (83–93) in Sierra Leone, and 140% (135–147) in Liberia in 2014. This increase is equivalent to 3·5 million (95% credible interval 2·6 million to 4·9 million) additional untreated cases, with 10 900 (5700–21 400) additional malaria-attributable deaths. Mass drug administration and distribution of insecticide-treated bednets timed to coincide with the 2015 malaria transmission season could largely mitigate the effect of Ebola virus disease on malaria. Interpretation These findings suggest that untreated malaria cases as a result of reduced health-care capacity probably contributed substantially to the morbidity caused by the Ebola crisis. Mass drug administration can be an effective means to mitigate this burden and reduce the number of non-Ebola fever cases within health systems. Funding UK Medical Research Council, UK Department for International Development, Bill & Melinda Gates Foundation.

Clinical, virological, and biological parameters associated with outcomes of Ebola virus infection in Macenta, Guinea

“…The incidence of malaria was similar in all patients, regardless of EBOV infection status, and was particularly high. This incidence is consistent with the high rates of mortality unrelated to EVD observed in forested areas of Guinea during the outbreak, with most of these deaths due to untreated malaria and measles (13)(14)(15). In contrast, no increase in mortality was associated with coinfection with P. falciparum in another study in Guinea (16), and a recent report described a reverse trend and suggested that coinfection may …”

The Sendai Framework for Disaster Risk Reduction: Renewing the Global Commitment to People’s Resilience, Health, and Well-being

“…The health disaster resulted in severe budget cuts to non-Ebola-related health services and a significant reduction in the use of health services owing to fears of cross-infection. As a result, more people are estimated to have died from childbirth, malaria, and AIDS, as well as other diseases (Walker et al 2015).…”

Timing and utilization of antenatal care services in Liberia: Understanding the pre-Ebola epidemic context

“…Population-based studies of maternal health service utilization in SSA have supported the Andersen model, suggesting an appraised need for services based on predisposing factors and enabling factors (Arthur, 2012;Dixon et al, 2014;Singh et al, 2014). Yet, in the context of the Ebola epidemic, the absence of health care providers offering relevant services, the inability to differentiate between Ebola and other febrile diseases at onset, and the fear of contracting Ebola at a health facility can also prevent pregnant women from seeking reproductive health services (Davtyan et al, 2014;Walker et al, 2015;Men endez et al, 2015).…”

“…In Liberia, the stigma that was associated with pregnant women during the epidemic draws attention to a need to understand how psychosocial factors may influence health service use in context (Weiss and Ramakrishna, 2006;Link and Phelan, 2006;Walker et al, 2015;Men endez et al, 2015;Delamou et al, 2014). Consequently, this analysis is informed by Goffman's (1963) conceptualization of stigma as a powerful, discrediting and tainting social label that fundamentally changes the way individuals' view themselves or are viewed by other people.…”