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"'I'm a Health Worker' - Abduaraman Gidi" made by IntraHealth International.

Melanie Morrow and Allyson Nelson*

Background and Rationale

Community health workers (CHWs) are vital to country strategies to achieve universal health coverage (UHC). As health systems come to rely on CHWs to deliver a growing number of interventions and activities, the potential for overburdening them with unrealistic expectations increases. Limited human and financial resources, combined with a lack of tools to operationalize context-specific considerations for planning CHW workload, can lead to wishful thinking when it comes to defining CHW scopes of work, how many CHWs to engage, and expectations for population-level impact.

In terms of how many CHWs to deploy relative to the population size, global benchmarks are difficult to identify, given variability in context and the number and types of services that CHWs may offer. The World Health Organization (WHO) Global Health Worker Alliance’s 2017 review of evidence concluded that the “estimation for an optimal population size would depend on various factors including the number and type of services and the actual time required for CHWs to complete their assigned tasks.”1 The resulting WHO Guideline on Health Policy and System Support to Optimize Community Health Worker Programmes2 suggests that most countries use the criteria outlined below to determine target population size.

The CHW Coverage and Capacity (C3) Tool takes into consideration many of these variables to addresses strategic and operational challenges associated with CHW planning. Although imperfect, it offers a reality check with respect to the potential overloading of CHWs relative to the combination of activities and population coverage assigned to them—and conversely, the approximate number of CHWs needed according to the scenarios modeled using the tool.

Purpose and Objectives

The C3 Tool uses Excel to model options for CHW program design with respect to CHW time allocation, workload, and targeted population coverage of interventions, among other variables. The tool is designed to help health planners approach analysis from one of two sides: (1) to determine the approximate number of CHWs required to efficiently provide specified health interventions, or (2) to define, rationalize, and optimize the effective level of coverage for and mix of activities/interventions that a predetermined number of CHWs undertake for a given population.

Figure 1: The C3 Tool is used as part of a decision-making process.



Eric Sarriot (Save the Children) and Melanie Morrow (ICF) originally developed the C3 concept and process, and Bill Winfrey (Avenir Health) developed the tool in Excel under the USAID-funded Maternal and Child Survival Program (MCSP). The tool was beta-tested in mainland Tanzania and over the course of its evolution, was also applied in Egypt, Sierra Leone, Rwanda and Zanzibar. Early design of the C3 Tool was adapted to improve consistency and complementarity with the Community Health Planning and Costing Tool (CHPCT). Refinements have been made to the C3 Tool in the course of applying it in each new setting.

Tool Description

The C3 Tool serves to improve policy and management decisions, which inherently deal with a substantial amount of uncertainty and contextual variability. For this reason, the C3 Tool uses as much hard data as is available but does not hesitate to use “rough measures of the right things”3 and assumptions about the value of key variables, for example in time management.

The C3 Tool can be used for planning, testing assumptions and scenario building, as a basis for costing, and producing evidence for advocacy:

1. Planning community health programs that will use CHWs at district, subnational, and/or national levels

Note: the C3 Tool does not seek to provide a mathematical blueprint for national planners to guide regional plans for how CHWs utilize their time, or even a regional blueprint for district and local plans. The C3 Tool only seeks to establish rational and realistic parameters for the planners to allow effective adaptive management by supervisors and managers.

2. Testing the assumptions stated in existing or draft CHW program plans to determine:

  • Is the CHW plan rational?
  • Is the CHW plan realistic?
  • Options for prioritizing CHW activities to fit available resources

3. Scenario building and hypothesis testing regarding CHW workload and coverage for up to six cadres of CHWs:

  • Decide on the number of CHWs required to efficiently carry out specified health interventions.
  • Define, rationalize, and optimize the effective level of coverage for--and mix of--activities/interventions that a set number of CHWs can undertake at a given geographic scale.
  • Identify the package of services that the CHWs can deliver for optimal coverage and outcomes needed based on the overall population size for a district, region, state, etc., within a national area.
  • Make decisions about distribution of workload across various CHW types.
  • Determine proportion of needed services that could be delivered by CHWs in contrast to other health care providers

4. Conducting a preliminary exercise to inform separate costing (national-, regional-, or district-level) activities based on the number of CHWs required to meet the coverage intended

5. Advocating for CHW programming

The C3 Tool complements other management tools, yielding a more complete picture for planners. For example, reproductive, maternal, newborn, and child health mortality modeling tools, such as the Lives Saved Tool,4 can help with intervention prioritization by projecting the estimated number of lives that could be saved if population coverage of specific interventions were achieved. In contrast, the C3 Tool helps planners understand how many CHWs will be needed to carry out evidence-informed policies and make rational decisions with respect to workload. Other tools exist for costing, such as the CHPCT.5


The C3 Tool is intended for CHW program planners at national and subnational levels in low- and middle- income countries, including district health teams adequately supported to use it. The tool is also valuable for technical assistance providers supporting ministries of health to optimize their CHW workforce. The C3 Tool is best applied in conjunction with champions who are well positioned at appropriate levels of influence to support data gathering, consensus building, and ultimate decision-making based on the tool’s outputs. Once the bulk of underlying program information has been entered, it is then easier for others to continue to model scenarios of interest for ongoing application.


Application of the tool involves engagement with CHW program decision makers and implementers to agree on the data and assumptions being used, scenarios to be tested, and interpretation of the output to inform feasible program strategy and operational plans. Because it combines modeling with programmatic and management discussions (see figure, above), using the C3 Tool requires combining two sets of skills: ability to navigate its Excel interface as well as ability to engage in programmatic and operational discussions.

Example Application: Zanzibar

In 2018, the Zanzibar Ministry of Health (MOH) and the President's Office Regional Administration, Local Government and Special Departments (PORALGSD) initiated a process of review and update of the National Community Health Strategy (CHS). This effort was supported by D-tree International, with funding from the Fondation Botnar, in close collaboration with other partners including UNICEF and Save the Children. Zanzibar’s existing CHS was approved in 2011; one major component of the updated CHS was to be the inclusion of community health volunteers as a pillar of Zanzibar’s Community Health Strategy.

The new national CHV program, named “Jamii ni Afya” (Community is Health), grew out of multiple community health volunteer programs that were implemented in Zanzibar over the past decade and institutionalizes a national, standard CHV cadre who will provide high-quality RMNCAH, nutrition, and early childhood development services to all Zanzibaris.

In designing the structure of the national CHV workforce, a key question the MOH needed to answer was “How many CHVs do we need to reach all communities in Zanzibar?” The answer had to take into consideration the services the CHVs would provide, the size of their catchment population, and the amount of work they would be expected to do on a monthly basis. To answer this question, D-tree International supported the MOH to use the C3 Tool, designed by the USAID/Maternal and Child Survival Program. Together, we reviewed the package of services the CHVs would provide. We estimated the number of visits individuals would receive, and the time each visit would take. We also developed assumptions for the travel time per visit, and the other activities CHVs would be engaged in including vaccination and mass drug administration campaigns, monthly meetings with their supervisors, and group counseling sessions. Then we agreed on a target level of coverage of each service for the population in need and on the estimated workload that would be feasible for each CHV (18 hours per week). From this point, we were able to adjust the catchment population and determine the number of CHVs needed to provide a certain level of coverage of community health services nationwide. Our final figures estimated that 2,200 CHVs could reach approximately 90% coverage of all services, working 18 hours per week, with a catchment population of 725 persons.

Figure 2: C3 Tool output, as modeled in Zanzibar, showing the percent of planned activities that can be implemented in three different scenarios analyzed using the tool, each with one cadre of CHV. The second and third scenarios reflect over and underutilization of the CHVs’ available time, compared to the first scenario deemed the “best package”.

A broader group of stakeholders from the MOH and PORALGSD reviewed the assumptions and estimates produced by the C3 Tool and decided to use the results as the foundation of the CHV program structure in the CHS. The CHV package of services, approximate catchment population, and number of CHVs that should be deployed are now included in the Zanzibar Community Health Strategy based on the C3 results6. The results of the C3 Tool pertaining to workload were also used to determine an acceptable monthly performance-based incentive for CHVs. Finally, the results from the C3 Tool were translated into the CHPCT, where the entire CHS and implementation of Jamii ni Afya was costed. The output from the CHPCT tools is being used to develop costed implementation plans and a longer-term investment case for the CHV program.

The updated CHS should be validated and approved by the MOH and PORALGSD by the end of 2019. The launch and scale up of the Jamii ni Afya CHV program is planned for 2019-2020.

Figure: C3 Tool output, ranking intervention activities from most to least time consuming, as modeled in Zanzibar.

Scale up

To facilitate use of the C3 Tool by others, MCSP developed an accompanying user guide. Readers interested in accessing the tool and the user guide can find them online in the MCSP Resource Center.

Authors affiliations

  • Melanie Morrow: Community Health and Civil Society Engagement Team Lead, Maternal and Child Survival Program/ICF
  • Allyson Nelson:   Program Manager, D-tree International

*Note on authorship/source material: This blog is based extensively on content from the CHW Coverage and Capacity Tool User Guide, as excerpted and adapted by Melanie Morrow (ICF).  The Zanzibar case example was written by Allyson Nelson (D-tree International).


1 Davis Balestracci. Data Sanity. A quantum leap to unprecedented results. 326 pages. Medical Group Management Association; 1 edition (January 1, 2009):

2 Center for Evidence and Implementation. 2017. Systematic Reviews to inform guidelines on health policy and system support to optimise community health worker programmes. PICO 10. In the context of practicing community health worker (CHW) programmes, should there be a target population size versus not? Final report to the World Health Organisation Guideline Development Group.

3 World Health Organization (WHO). 2018. WHO Guideline on Health Policy and System Support to Optimize Community Health Worker Programmes. Geneva: WHO.

4 Johns Hopkins Bloomberg School of Public Health, Bill & Melinda Gates Foundation. Lives Saved Tool.

5 Management Sciences for Health/UNICEF. Community Health Planning and Costing Tool.

6 Noting that due to geographic and other reasons, some flexibility in catchment population would be required, the CHS states that the catchment area should be 500-1,000 persons.

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