Health-care worker mortality and the legacy of the Ebola epidemic.

The recent outbreak of Ebola in West Africa will leave a legacy signifi cantly deeper than the morbidity and mortality caused directly by the disease. Ebola deaths have been disproportionately concentrated among health personnel. By May, 2015, 0·02% of Guinea’s population had died due to Ebola, compared with 1·45% of the country’s doctors, nurses, and midwives. In Liberia and Sierra Leone, the differences are more dramatic, with 0·11% and 0·06% of the general population killed by Ebola versus 8·07% of the health-care workers in Liberia, and 6·85% in Sierra Leone. The fact that health-care workers are at greater risk of contracting Ebola will exacerbate existing skill shortages in countries that had few health personnel to begin with. We modelled how the loss of healthcare workers—defi ned here as doctors, nurses, and midwives—to Ebola might affect maternal, infant, and under-5 mortality in Guinea, Liberia, and Sierra Leone, with the aim of characterising the order of magnitude of likely effects, not providing specific pre dictions. We combined data on: (1) health-care worker deaths from Ebola; (2) the stock of healthcare workers pre-Ebola; (3) maternal, infant, and under-5 mortality rates for each country, pre-Ebola; and (4) coefficients of health-care worker mortality, which capture the relation between health-care workers in a given country and diff erent mortality rates (ie, maternal, infant, and under-5 mortality). For each of the three countries, we first calculated how many doctors, nurses, and midwives combined have died due to Ebola per 1000 of the population. We multiplied each preEbola mortality rate (maternal, infant, and under-5) by 1 minus this fraction, multiplied by the health-care worker mortality coeffi cient. We then translated this fi gure into the percentage change in mortality relative to preEbola rates (appendix). We constructed bounds based on the 95% CIs of the estimated coeffi cients of health-care worker mortality. These incorporate the estimation uncertainty associated with the health-care worker mortality coeffi cients and the pre-Ebola mortality rates, under the assumption that the latter uncertainty is constant across countries and over the period between the estimation of the health-care worker mortality coefficients (2006) and the present (2015). However, we were unable to account for the uncertainty surrounding the measurement of health-care worker mortality owing to a lack of data. As of late May, 2015, Guinea, Liberia, and Sierra Leone, respectively, had lost 78, 83, and 79 doctors, nurses, and midwives to Ebola. The largest eff ects of these health-care worker deaths for all three countries were on maternal mortality (table), namely increases of 38% (95% CI 26–50) in Guinea, 74% (51–97) in Sierra Leone, and as large as 111% (76–145) in Liberia, relative to pre-Ebola rates. Estimated eff ects on infant and under-5 mortality ranged from an increase of 7–20% and 10–28% across countries, respectively. However, in both of the latter cases the health-care worker mortality coeffi cients used were not statistically signifi cant in the original study and the range between the upper and lower bounds of the 95% CIs includes a zero eff ect (table). Combining these estimates with the most recent population numbers and rate of livebirths in each country pre-Ebola suggests that an additional 4022 women would die per year in childbirth as a result of doctors, nurses, and midwives lost to Ebola. This would bring the countries back to rates of maternal mortality last seen in 2000 in Guinea and Sierra Leone, and 1995 in Liberia. These mortality estimates have limitations. The model’s use of crosscountry mortality coeffi cients assumes that the eff ect of health-care worker supply on maternal, infant, and under-5 mortality in Guinea, Liberia, and Sierra Leone is similar to the cross-country average and has not changed since those coeffi cients were estimated. This work further assumes that unmeasured elements of health systems (such an overall measure of quality), associated with both health-care worker density and mortality, are not driving the result. Data limitations make it difficult to account for these unmeasured factors, See Online for appendix