Universal health coverage requires an adequate health workforce, including community health workers (CHWs) to reach rural communities. To improve healthcare access in rural areas, in 2010 the Government of Zambia implemented a national CHW strategy that introduced a new cadre of healthcare workers called community health assistants (CHAs). After 1 year of training the pilot class of 307 CHAs deployed in September 2012. This paper presents findings from a process evaluation of the barriers and facilitators of implementation of the CHA pilot, along with how evidence was used to guide ongoing implementation and scale-up decisions. Qualitative inquiry was used to assess implementation during the first 6 months of the program rollout, with 43 in-depth individual and 32 small group interviews across five respondent types: CHAs, supervisors, volunteer CHWs, community members, and district leadership. Potential 'implementation moderators' were explored using deductive coding and thematic analysis of participant perspectives on community acceptance of CHAs, supervision support mechanisms, and coordination with volunteer CHWs, and health system integration of a new cadre. Community acceptance of CHAs was generally high, but coordination between CHAs and existing volunteer CHWs presented some challenges. The supervision support system was found to be inconsistent, limiting assurance of consistent quality care delivered by CHAs. Underlying health system weaknesses regarding drug supply and salary payments furthermore hindered incorporation of a new cadre within the national health system. Recommendations for implementation and future scale based on the process evaluation findings are discussed.

BackgroundThe Zambia Ministry of Health (MOH) recruited and trained a new cadre of Community Health Assistants (CHAs) as part of its National Community Health Strategy. The inaugural class of 307 CHAs completed one year of training in July 2012 and deployed to their communities.MethodsThe impact of the CHA program on the volume and type of health services provided at health posts and their respective referral health centers was measured with a non-randomized difference-in-differences design. Monthly health service provision data was collected for 12 months before and after CHA deployment at 8 health posts along with 8 referral health centers. The analysis controlled for seasonality, changes in non-CHA staffing, and periodic regional child health campaigns, and used facility-level fixed effects.ResultsDeploying two CHAs to a health post did not lead to a statistically-discernible increase in services at the intervention facilities. Health services provided at referral health centers increased by 697.9 services per month (95% CI: 131.4 to 1,264.3, p = .016), and combined services (at health posts and referral health centers) increased by 848.6 services per month (95% CI: 178.2 to 1,519.1, p = .013).ConclusionIn this pilot, the addition of CHAs in rural areas increased health service provision at referral health facilities and at facilities overall, shifting the burden of basic health services away from more highly trained health workers. Shifting tasks to lesser-trained, less-expensive cadres like the CHAs, policymakers can rapidly improve access to care with constrained budgets. Evaluations measuring the direct impact of lower level cadres without accounting for task-shifting may underestimate their contribution to the health workforce.

Abstractobjective A critical shortage of human resources for health in Zambia remains a great challenge. In response, the Zambian Ministry of Health developed a national community health assistant (CHA) programme, aiming to create a well-trained and motivated community-based health workforce. This study assessed whether CHAs increased treatment rates for diarrhoea, confirmed malaria or pneumonia in the first programme year.methods This study used a quasi-experimental difference-in-difference design, comparing changes in the catchment areas of health posts with CHAs to those without. Baseline and end line household surveys were conducted to measure the proportion of children under 5 years treated for diarrhoea, malaria or pneumonia in the 2 weeks before the survey and immunisation rates and malaria rapid diagnostic test rates.results We surveyed 2330 women with children under five from the intervention area and 2314 from comparison areas at baseline and end line. Treatment for diarrhoea, malaria or pneumonia increased by 18.0% (P < 0.01) and 23.5% (P < 0.01) in the intervention and comparison groups, respectively, but DID analysis was not significant (P = 0.27). The proportion of fully immunised children grew by 7.5% in the intervention, but shrank by 7.5% in the comparison group (DID: 0.14; 95% CI 0.12-0.16, P < 0.01).conclusion Although we observed no significant difference between the intervention and comparison groups in the DID estimates for the primary outcome, there were significant increases after one year in treatment for all three diseases in the intervention group from baseline to end line and in the proportion of fully immunised children.

Building a health workforce in low-income countries requires a focused investment of time and resources, and ministries of health need tools to create staffing plans and prioritize spending on staff for overburdened health facilities. In Zambia a demand-based workload model was developed to calculate the number of health workers required to meet demands for essential health services and inform a rational and optimized strategy for deploying new public-sector staff members to the country's health facilities. Between 2009 and 2011 Zambia applied this optimized deployment policy, allocating new health workers to areas with the greatest demand for services. The country increased its health worker staffing in districts with fewer than one health worker per 1,000 people by 25.2 percent, adding 949 health workers to facilities that faced severe staffing shortages. At facilities that had had low staffing levels, adding a skilled provider was associated with an additional 103 outpatient consultations per quarter. Policy makers in resource-limited countries should consider using strategic approaches to identifying and deploying a rational distribution of health workers to provide the greatest coverage of health services to their populations.

IntroductionThe COVID-19 pandemic in Mexico began at the end of February 2020. An essential component of control strategies was to reduce mobility. We aimed to evaluate the impact of mobility on COVID- incidence and mortality rates during the initial months of the pandemic in selected states.MethodsCOVID-19 incidence data were obtained from the Open Data Epidemiology Resource provided by the Mexican government. Mobility data was obtained from the Observatory for COVID-19 in the Americas of the University of Miami. We selected four states according to their compliance with non-pharmaceutical interventions and mobility index. We constructed time series and analyzed change-points for mobility, incidence, and mortality rates. We correlated mobility with incidence and mortality rates for each time interval. Using mixed-effects Poisson models, we evaluated the impact of reductions in mobility on incidence and mortality rates, adjusting all models for medical services and the percentage of the population living in poverty.ResultsAfter the initial decline in mobility experienced in early April, a sustained increase in mobility followed during the rest of the country-wide suspension of non-essential activities and the return to other activities throughout mid-April and May. We identified that a 1% increase in mobility yielded a 5.2 and a 2.9% increase in the risk of COVID-19 incidence and mortality, respectively. Mobility was estimated to contribute 8.5 and 3.8% to the variability in incidence and mortality, respectively. In fully adjusted models, the contribution of mobility to positive COVID-19 incidence and mortality was sustained. When assessing the impact of mobility in each state compared to the state of Baja California, increased mobility conferred an increased risk of incident positive COVID-19 cases in Mexico City, Jalisco, and Nuevo León. However, for COVID-19 mortality, a differential impact of mobility was only observed with Jalisco and Nuevo León compared to Baja California.ConclusionMobility had heterogeneous impacts on COVID-19 rates in different regions of Mexico, indicating that sociodemographic characteristics and regional-level pandemic dynamics modified the impact of reductions in mobility during the COVID-19 pandemic. The implementation of non-pharmaceutical interventions should be regionalized based on local epidemiology for timely response against future pandemics.