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Can volunteer community health workers decrease child morbidity and mortality in southwestern Uganda? An impact evaluation

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Brenner, J. L., J. Kabakyenga, et al. (2011). "Can volunteer community health workers decrease child morbidity and mortality in southwestern Uganda? An impact evaluation." PLoS ONE 6(12).

Background: The potential for community health workers to improve child health in sub-Saharan Africa is not well understood. Healthy Child Uganda implemented a volunteer community health worker child health promotion model in rural Uganda. An impact evaluation was conducted to assess volunteer community health workers' effect on child morbidity, mortality and to calculate volunteer retention.

Methodology/Principal Findings: Two volunteer community health workers were selected, trained and promoted child health in each of 116 villages (population ~61,000) during 2006-2009. Evaluation included a household survey of mothers at baseline and post-intervention in intervention/control areas, retrospective reviews of community health worker birth/child death reports and post-intervention focus group discussions. Retention was calculated from administrative records. Main outcomes were prevalence of recent child illness/underweight status, community health worker reports of child deaths, focus group perception of effect, and community health worker retention. After 18-36 months, 86% of trained volunteers remained active. Post-intervention surveys in intervention households revealed absolute reductions of 10.2% [95%CI (-17.7%, -2.6%)] in diarrhea prevalence and 5.8% [95%CI (-11.5%, -0.003%)] in fever/malaria; comparative decreases in control households were not statistically significant. Underweight prevalence was reduced by 5.1% [95%CI (-10.7%, 0.4%)] in intervention households. Community health worker monthly reports revealed a relative decline of 53% in child deaths (<5 years old), during the first 18 months of intervention. Focus groups credited community health workers with decreasing child deaths, improved care-seeking practices, and new income-generating opportunities.

Conclusions/Significance: A low-cost child health promotion model using volunteer community health workers demonstrated decreased child morbidity, dramatic mortality trend declines and high volunteer retention. This sustainable model could be scaled-up to sub-Saharan African communities with limited resources and high child health needs.

Why the focus on direct impact data?

A common challenge from policy makers, funders, community members, people directly experiencing development issues, and governments is: Demonstrate your Impact. Prove that what you are doing works. The high quality, highly credible data presented on the cards below is designed to help you answer that question for your social change, behaviour change, community engagement, communication and media for development, strategy formulation, policy engagement and funding initiatives. At this link filter the research data to your specific interests and priorities

Why a playing cards design?

There is a physical pack of cards with this data (to get a copy please request through the comment form for any card). The card approach allows for easy identification and selection of relevant direct impact data in any context. For example if talking with a donor and you need to identify proof of impact say "take a look at the 7 of Hearts". Quick access can be provided to high-quality data for many areas of your work – funding, planning, policy, advocacy, community dialogue, training, partner engagement, and more. A card deck is also engaging, easy to use and share, a conversation starter, and a resource - and they are fun and different. So we kept that design for the online images as it can serve similar purposes. 

What are the criteria for inclusion?

The impact data presented meets the following high standard for inclusion criteria:

  • Positive change or trend in a priority development issue;
  • Social change or behaviour change strategy or process;
  • Randomized Control Trial or Systematic Review methodology;
  • High quality peer review journal published;
  • Numeric impact data point
  • Published since 2010.