Applying WHO COVID-19 workforce estimate tools remotely in an African context: a case report from Mali and Kenya.

BACKGROUND: The COVID-19 pandemic has increased the burden on health systems, particularly in low- and middle-income countries, where health systems already struggle. To meet health workforce planning needs during the pandemic, IntraHealth International used two tools created by the World Health Organization (WHO) Regional Office for Europe. The Health Workforce Estimator (HWFE) allows the estimation of the quantity of health workers needed to treat patients during a surge, and the Adaptt Surge Planning Support Tool helps to predict the timing of a surge in cases and the number of health workers and beds needed for predicted caseload. These tools were adapted to fit the African context in a rapid implementation over 5 weeks in one region in Mali and one region in Kenya with the objective to test the feasibility of adapting these tools, which use a Workload Indicators of Staffing Need (WISN)-inspired human resources management methodology, to obtain daily and surge projections of COVID-19 human resources for health needs. CASE PRESENTATION: Using a remote team in the US and in-country teams in Mali and Kenya, IntraHealth enacted a phased plan to gather stakeholder support, collect data related to health systems and COVID-19 cases, populate data into the tools, verify modeled results with results on the ground, enact policy measures to meet projected needs, and conduct national training workshops for the ministries of health. CONCLUSIONS: This phased implementation in Mali and Kenya demonstrated that the WISN approach applied to the Health Workforce Estimator and Adaptt tools can be readily adapted to the local context for African countries to rapidly estimate the number of health workers and beds needed to respond to the predicted COVID-19 pandemic caseload. The results may also be used to give a proxy estimate for needed health supplies-e.g., oxygen, medications, and ventilators. Challenges included accurate and timely data collection and updating data. The success of the pilot can be attributed to the adapted WHO tools, the team composition in both countries, access to human resources data, and early support of the ministries of health, with the expectation that this methodology can be applied to other country contexts.

A national atlas of tsetse and African animal trypanosomosis in Mali.

BACKGROUND: Tsetse-transmitted trypanosomosis is a deadly, neglected tropical disease and a major challenge for mixed crop-livestock agriculture in sub-Saharan Africa. It is caused by several species of the genus Trypanosoma. Information on the occurrence of tsetse flies and African animal trypanosomosis (AAT) is available for different areas of Mali. However, these data have never been harmonized and centralized, which prevents the development of comprehensive epidemiological maps and constrains an evidence-based planning of control actions. To address this challenge, we created a dynamic geo-spatial database of tsetse and AAT distribution in Mali. METHODS: A digital repository containing epidemiological data collected between 2000 and 2018 was assembled. In addition to scientific publications, the repository includes field datasheets, technical reports and other grey literature. The data were verified, harmonized, georeferenced and integrated into a single spatially-explicit database. RESULTS: For the tsetse component, approximately 19,000 trapping records, corresponding to 6000 distinct trapping locations and 38,000 flies were included in the database. Glossina palpalis gambiensis was the most widespread and abundant species, and it was found in the southern, southern-central and western parts of the country. Glossina tachinoides was only found in the South. Only a few specimens of Glossina morsitans submorsitans were detected. For the AAT component, approximately 1000 survey records were included, corresponding to 450 distinct survey sites and 37,000 tested bovines. AAT was found in all surveyed regions, although data for the tsetse-free North and North-East are lacking. Trypanosoma vivax and Trypanosoma congolense were the dominant species, while Trypanosoma brucei infections were much less numerous. CONCLUSIONS: The atlas of tsetse and AAT in Mali provides a synoptic view of the vector and disease situation at the national level. Still, major geographical gaps affect the North, the North-East and the West, and there is also a severe lack of data over the past five years. Trypanosomosis remains a major animal health problem in Mali. However, despite its prevalence and distribution, monitoring and control activities are presently very limited. Efforts should be made to strengthen the progressive control of AAT in Mali, and the atlas provides a new tool to identify priority areas for intervention.