Dataset Information

Supply-side and demand-side factors influencing uptake of malaria testing services in the community: lessons for scale-up from a post-hoc analysis of a cluster randomised, community-based trial in western Kenya.

ABSTRACT:

Objectives

Maximising the impact of community-based programmes requires understanding how supply of, and demand for, the intervention interact at the point of delivery.

Design

Post-hoc analysis from a large-scale community health worker (CHW) study designed to increase the uptake of malaria diagnostic testing.

Setting

Respondents were identified during a household survey in western Kenya between July 2016 and April 2017.

Participants

Household members with fever in the last 4 weeks were interviewed at 12 and 18 months post-implementation. We collected monthly testing data from 244 participating CHWs and conducted semistructured interviews with a random sample of 70 CHWs.

Primary and secondary outcome measures

The primary outcome measure was diagnostic testing before treatment for a recent fever. The secondary outcomes were receiving a test from a CHW and tests done per month by each CHW.

Results

55% (n=948 of 1738) reported having a malaria diagnostic test for their recent illness, of which 38.4% were tested by a CHW. Being aware of a local CHW (adjusted OR=1.50, 95% CI: 1.10 to 2.04) and belonging to the wealthiest households (vs least wealthy) were associated with higher testing (adjusted OR=1.53, 95% CI: 1.14 to 2.06). Wealthier households were less likely to receive their test from a CHW compared with poorer households (adjusted OR=0.32, 95% CI: 0.17 to 0.62). Confidence in artemether-lumefantrine to cure malaria (adjusted OR=2.75, 95% CI: 1.54 to 4.92) and perceived accuracy of a malaria rapid diagnostic test (adjusted OR=2.43, 95% CI: 1.12 to 5.27) were positively associated with testing by a CHW. Specific CHW attributes were associated with performing a higher monthly number of tests including formal employment, serving more than 50 households (vs <50) and serving areas with a higher test positivity. On demand side, confidence of the respondent in a test performed by a CHW was strongly associated with seeking a test from a CHW.

Conclusion

Scale-up of community-based malaria testing is feasible and effective in increasing uptake among the poorest households. To maximise impact, it is important to recognise factors that may restrict delivery and demand for such services.

Trial registration number

NCT02461628; Post-results.

SUBMITTER: Kirui J

PROVIDER: S-EPMC10410802 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Supply-side and demand-side factors influencing uptake of malaria testing services in the community: lessons for scale-up from a post-hoc analysis of a cluster randomised, community-based trial in western Kenya.

Kirui Joseph J Malinga Josephine J Sang Edna E Ambani George G Abel Lucy L Nalianya Erick E Namae Jane J Boyce Matthew M Laktabai Jeremiah J Menya Diana D O'Meara Wendy W

BMJ open 20230626 6

<h4>Objectives</h4>Maximising the impact of community-based programmes requires understanding how supply of, and demand for, the intervention interact at the point of delivery.<h4>Design</h4>Post-hoc analysis from a large-scale community health worker (CHW) study designed to increase the uptake of malaria diagnostic testing.<h4>Setting</h4>Respondents were identified during a household survey in western Kenya between July 2016 and April 2017.<h4>Participants</h4>Household members with fever in t ...[more]

PMID: 37369403

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Dataset Information

Supply-side and demand-side factors influencing uptake of malaria testing services in the community: lessons for scale-up from a post-hoc analysis of a cluster randomised, community-based trial in western Kenya.

Objectives

Design

Setting

Participants

Primary and secondary outcome measures

Results

Conclusion

Trial registration number

Publications

Supply-side and demand-side factors influencing uptake of malaria testing services in the community: lessons for scale-up from a post-hoc analysis of a cluster randomised, community-based trial in western Kenya.

Similar Datasets

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