BackgroundSkilled attendance at delivery is recognized as one of the most important factors in preventing maternal death. However, more than 50% of births in Kenya still occur in non-institutional locations supported by family members and/or traditional birth attendants (TBAs). To improve this situation, a study of the determinants of facility delivery, including individual, family and community factors, was necessary to consider effective intervention in Kenya.MethodsThis study was conducted to identify the factors which influence the place of delivery in rural western Kenya, and to recommend ways to improve women’s access to skilled attendants at delivery. A community-based cross-sectional survey was carried out from August to September 2011 in all 64 sub-locations which were covered by community health workers (CHWs). An interviewer-administered questionnaire on seventeen comprehensive variables was administered to 2,560 women who had children aged 12–24 months.ResultsThe response rate was 79% (n = 2,026). Of the respondents, 48% of births occurred in a health facility and 52% in a non-institutional location. The significant determinants of facility delivery examined using multivariate analysis were: maternal education level, maternal health knowledge, ANC visits, birth interval, economic status of household, number of household members, household sanitation practices and traveling time to nearest health facility.ConclusionsThe results suggest that the involvement of TBAs to promote facility delivery is still one of the most important strategies. Strengthening CHWs’ performance by focusing on a limited number of topics and clear management guidance might also be an effective intervention. Stressing the importance of regular attendance at ANC (at least four times) would be effective in enhancing motivation for a facility delivery. Based on our findings, those actions to improve the facility delivery rate should focus more on pregnant women who have a low education level, poor health knowledge and short pregnancy spacing. In addition, women with low economic status, a large number of family members and a long distance to travel to a health facility should also be targeted by further interventions.

BackgroundSeveral African and South Asian countries are currently investing in new cadres of community health workers (CHWs) as a major part of strategies aimed at reaching the Millennium Development Goals. However, one review concluded that community health workers did not consistently provide services likely to have substantial effects on health and that quality was usually poor. The objective of this research was to assess the CHWs’ performance in Western Kenya and describe determinants of that performance using a multilevel analysis of the two levels, individual and supervisor/community.MethodsThis study conducted three surveys between August and September 2011 in Nyanza Province, Kenya. The participants of the three surveys were all 1,788 active CHWs, all their supervisors, and 2,560 randomly selected mothers who had children aged 12 to 23 months. CHW performance was generated by three indicators: reporting rate, health knowledge and household coverage. Multilevel analysis was performed to describe the determinants of that performance.ResultsThe significant factors associated with the CHWs’ performance were their marital status, educational level, the size of their household, their work experience, personal sanitation practice, number of supervisions received and the interaction between their supervisors’ better health knowledge and the number of supervisions.ConclusionA high quality of routine supervisions is one of the key interventions in sustaining a CHW’s performance. In addition, decreasing the dropout rate of CHWs is important both for sustaining their performance and for avoiding the additional cost of replacing them. As for the selection criteria of new CHWs, good educational status, availability of supporters for household chores and good sanitation practices are all important in selecting CHWs who can maintain their high performance level.

An MCH handbook was an effective tool for improving both health knowledge and health-seeking behavior in Kenya. The further distribution and utilization of an MCH handbook is expected to be an effective way to improve both maternal and child health.

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Background As countries make progress towards HIV epidemic control, there is increasing need to identify finer geographic areas to target HIV interventions. We mapped geographic clusters of new HIV diagnoses, and described factors associated with HIV-positive diagnosis, in order to inform targeting of HIV interventions to finer geographic areas and sub-populations. Methods We analyzed data for clients aged > 15 years who received home-based HIV testing as part of a routine public health program between May 2016 and July 2017 in Siaya County, western Kenya. Geospatial analysis using Kulldorff’s spatial scan statistic was used to detect geographic clusters (radius < 5 kilometers) of new HIV diagnoses. Factors associated with new HIV diagnosis were assessed in a spatially-integrated Bayesian hierarchical model. Results Of 268,153 clients with HIV test results, 2906 (1.1%) were diagnosed HIV-positive. We found spatial variation in the distribution of new HIV diagnoses, and identified nine clusters in which the number of new HIV diagnoses was significantly (1.56 to 2.64 times) higher than expected. Sub-populations with significantly higher HIV-positive yield identified in the multivariable spatially-integrated Bayesian model included: clients aged 20–24 years [adjusted relative risk (aRR) 3.45, 95% Bayesian Credible Intervals (CI) 2.85–4.20], 25–35 years (aRR 4.76, 95% CI 3.92–5.81) and > 35 years (aRR 2.44, 95% CI 1.99–3.00); those in polygamous marriage (aRR 1.84, 95% CI 1.55–2.16), or separated/divorced (aRR 3.36, 95% CI 2.72–4.08); and clients who reported having never been tested for HIV (aRR 2.35, 95% CI 2.02–2.72), or having been tested > 12 months ago (aRR 1.53, 95% CI 1.41–1.66). Conclusion Our study used routine public health program data to identify granular geographic clusters of higher new HIV diagnoses, and sub-populations with higher HIV-positive yield in the setting of a generalized HIV epidemic. In order to target HIV testing and prevention interventions to finer granular geographic areas for maximal epidemiologic impact, integrating geospatial analysis into routine public health programs can be useful.