and midwives – they again find a significant association between doctor density and all mortality rates, while the relationship for nurses is significant (and negative) only in the case of maternal mortality.<sup><u>18</u></sup> Farahani et al. are the first to use panel data in their analysis of 99 countries, which looks at the effect of doctor density on infant mortality. They find that adding one doctor for every 1,000 population is consistent with a significant reduction in infant mortality by about 30%, or 45% in the long-run.<sup><u>19</u></sup> While these recent studies - with their various functional forms - tend to converge on a significant negative association of both aggregate health care worker density and doctor density with mortality rates, they also converge in their inability to sufficiently account for other factors that may be driving mortality rates. Notably, there may be a selection problem such that countries with health systems which are weak in ways other than simply having few health care workers (e.g., low health expenditure, high geographic concentration of services, limited access to external resources, or inappropriate incentive and decision-making structures)<sup><u>17,18</u></sup> experience high mortality rates precisely due to these other weaknesses. Not only would a wider range of inputs to the production of health ideally be included in the models, but health care workers would preferably be separated from the factors likely to mediate the efficiency with which they are able to perform.<sup><u>18</u></sup> Data limitations make it difficult to account for these other factors, however, so while these studies acknowledge that the performance of health care workers will be dependent on these factors and note their exclusion as a shortcoming, they either argue that health care workers are the “glue” that allows the rest of the system to function,<sup><u>20</u></sup> or that the workers serve as a proxy for general health system resources.<sup><u>19</u></sup>

# **Methods**

This paper combines data from the following sources to model how the loss of health care workers to Ebola will affect non-Ebola mortality in Guinea, Liberia, and Sierra Leone: (1) current health care worker deaths from Ebola, disaggregated by country and occupation; (2) the stock of health care workers pre-Ebola, similarly disaggregated; (3) maternal, infant, and under-five mortality rates for each country, pre-Ebola; and (4) health care worker mortality coefficients, which capture the relationship between health care workers in a given country and different mortality rates (i.e., maternal mortality, infant mortality, and under-five mortality<sup>i</sup> ).

Addressing the source of each of these in turn, disaggregated data on health care worker deaths from Ebola in Guinea, Liberia, and Sierra Leone come from the World Health Organization (WHO), based on the Viral Haemorrhagic Fever database of each country.<sup><u>8</u></sup> We use data on the stock of health care workers from the WHO Global Health Workforce Statistics.<sup>ii</sup><sup><u>10</u></sup> Pre-Ebola mortality rates for each country come from the World Development Indicators (WDI).<sup><u>9</u></sup> We use coefficients from Speybroeck et al.<sup><u>18</u></sup> as our main estimates for the association between aggregate health care worker density (for doctors, nurses, and midwives, combined) and maternal, infant, 5