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Optimising the scale and deployment of community health workers (CHWs) is important for maximizing geographical accessibility of integrated primary health care (PHC) services. Yet little is known about approaches for doing so.We used geospatial analysis to model optimised scale-up and deployment of CHWs in Mali, to inform strategic and operational planning by the Ministry of Health and Social Development. Accessibility catchments were modelled based on travel time, accounting for barriers to movement. We compared geographic coverage of the estimated population, under-five deaths, and plasmodium falciparum (Pf) malaria cases across different hypothetical optimised CHW networks and identified surpluses and deficits of CHWs compared to the existing CHW network.A network of 15843 CHW, if optimally deployed, would ensure that 77.3% of the population beyond 5 km of the CSCom (community health centre) and CSRef (referral health facility) network would be within a 30-minute walk of a CHW. The same network would cover an estimated 59.5% of U5 deaths and 58.5% of Pf malaria cases. As an intermediary step, an optimised network of 4500 CHW, primarily filling deficits of CHW in the regions of Kayes, Koulikoro, Sikasso, and Ségou would ensure geographic coverage for 31.3% of the estimated population. There were no important differences in geographic coverage percentage when prioritizing CHW scale-up and deployment based on the estimated population, U5 deaths, or Pf malaria cases.Our geospatial analysis provides useful information to policymakers and planners in Mali for optimising the scale-up and deployment of CHW and, in turn, for maximizing the value-for-money of resources of investment in CHWs in the context of the country’s health sector reform. Countries with similar interests in optimising the scale and deployment of their CHW workforce may look to Mali as an exemplar model from which to learn.

Little is known about the HIV-1 epidemic in Balkan countries. To fill the gap, we investigated the viral genetic diversity in Bulgaria, by sequencing and phylogenetic characterization of 86 plasma samples collected between 2002 and 2006 from seropositive individuals diagnosed within 1986-2006. Analysis of pol gene sequences assigned 51% of the samples to HIV-1 subtype B and 27% to subtype A1. HIV-1 subtype C, F, G, H, and a few putative recombinant forms were also found. Phylogenetic and molecular clock analysis showed a continuous exchange of subtype A and B between Bulgaria and Western as well as other Eastern European countries. At least three separate introductions of HIV-1 subtype A and four of HIV-1 subtype B have occurred within the past 25 years in Bulgaria. The central geographic location of Bulgaria, the substantial genetic heterogeneity of the epidemic with multiple subtypes, and the significant viral flow observed to and from the Balkan countries have the potential to modify the current HIV-1 epidemiological structure in Europe and highlight the importance of more extensive and continuous monitoring of the epidemic in the Balkans.