Simulating the council-specific impact of anti-malaria interventions: A tool to support malaria strategic planning in Tanzania

Runge, Manuela; Snow, Robert W.; Molteni, Fabrizio; Thawer, Sumaiyya G.; Amara, Mohamed; Mandike, Renata; Giorgi, Emanuele; Macharia, Peter M.; Smith, T.; Lengeler, Christian; Pothin, Emilie

doi:10.1371/journal.pone.0228469

Cited by 30 publications

(45 citation statements)

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“…It is also essential to set realistic targets and expectations on what modelling can and cannot deliver [6] in a given timeframe. The outputs of the process, described in [40], did ultimately not inform the 2017 concept note for the GFATM application as was initially foreseen. Neither the model outputs nor the NMCP were ready for that exercise because of tight deadlines and additional time required for the model calibration.…”

Section: Discussionmentioning

confidence: 98%

“…The sections below describe the non-technical process of applying mathematical modelling, its added value, challenges and lessons learned. The development of the modelling approach is described in [40] and the results of modelling application are included in the Supplementary Midterm Malaria Strategic Plan 2018-2020 [41].…”

Section: Country Application Mainland Tanzaniamentioning

confidence: 99%

“…First, there was no previous experience for country modelling available at that level of detail that could have guided the process and the type of required outputs. Second, methodological challenges led to extended times for model calibration and complicated uncertainty estimates around the predictions [40]. Uncertainty resides in model predictions.…”

Section: Challengesmentioning

confidence: 99%

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Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

Runge

Molteni

Mandike

et al. 2020

Malar J

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Background: More than ever, it is crucial to make the best use of existing country data, and analytical tools for developing malaria control strategies as the heterogeneity in malaria risk within countries is increasing, and the available malaria control tools are expanding while large funding gaps exist. Global and local policymakers, as well as funders, increasingly recognize the value of mathematical modelling as a strategic tool to support decision making. This case study article describes the long-term use of modelling in close collaboration with the National Malaria Control Programme (NMCP) in Tanzania, the challenges encountered and lessons learned. Case description: In Tanzania, a recent rebound in prevalence led to the revision of the national malaria strategic plan with interventions targeted to the malaria risk at the sub-regional level. As part of the revision, a mathematical malaria modelling framework for setting specific predictions was developed and used between 2016 and 2019 to (1) reproduce setting specific historical malaria trends, and (2) to simulate in silico the impact of future interventions. Throughout the project, multiple stakeholder workshops were attended and the use of mathematical modelling interactively discussed. Evaluation: In Tanzania, the model application created an interdisciplinary and multisectoral dialogue platform between modellers, NMCP and partners and contributed to the revision of the national malaria strategic plan by simulating strategies suggested by the NMCP. The uptake of the modelling outputs and sustained interest by the NMCP were critically associated with following factors: (1) effective sensitization to the NMCP, (2) regular and intense communication, (3) invitation for the modellers to participate in the strategic plan process, and (4) model application tailored to the local context. Conclusion: Empirical data analysis and its use for strategic thinking remain the cornerstone for evidence-based decision-making. Mathematical impact modelling can support the process both by unifying all stakeholders in one strategic process and by adding new key evidence required for optimized decision-making. However, without a long-standing partnership, it will be much more challenging to sensibilize programmes to the usefulness and sustained use of modelling and local resources within the programme or collaborating research institutions need to be mobilized.

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Section: Discussionmentioning

confidence: 98%

Section: Country Application Mainland Tanzaniamentioning

confidence: 99%

Section: Challengesmentioning

confidence: 99%

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Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

Runge

Molteni

Mandike

et al. 2020

Malar J

Self Cite

View full text Add to dashboard Cite

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“…In Tanzania, a review of the most recent population-based malaria indicator survey and health facility (HFs) information has shown the high heterogeneity of malaria endemicity within regions across the country [11,[27][28][29][30], underscoring the need to deploy appropriate interventions carefully. New approaches for malaria control are needed to sustain and accelerate progress towards elimination, and synthesis of the WHO-T3 initiative and the Chinese experience of surveillance and response offers a great opportunity for the identi cation of new approaches.…”

Section: Page 4/23mentioning

confidence: 99%

Effectiveness of the innovative 1,7-malaria reactive community-based testing and response (1, 7-mRCTR) approach on malaria burden reduction in Southeastern Tanzania

Mlacha

Wang²,

Chaki

et al. 2020

Preprint

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BackgroundIn 2015, a China-UK-Tanzania tripartite pilot project was implemented in southeastern Tanzania to explore a new model for reducing malaria burden and possibly scaling-out the approach into other malaria-endemic countries. The 1,7-malaria Reactive Community-based Testing and Response (1,7-mRCTR) which is a locally-tailored approach for reporting febrile malaria cases in endemic villages was developed to stop transmission and Plasmodium life-cycle. The (1,7-mRCTR) utilizes existing health facility data and locally trained community health workers to conduct community-level testing and treatment.MethodsThe pilot project was implemented from September 2015 to June 2018 in Rufiji District, southern Tanzania. The study took place in four wards, two with low incidence and two with a higher incidence. One ward of each type was selected for each of the control and intervention arms. The control wards implemented the existing Ministry of Health programmes. The 1,7-mRCTR activities implemented in the intervention arm included community testing and treatment of malaria infection. Malaria case-to-suspect ratios at health facilities (HF) were aggregated by villages, weekly to identify the village with the highest ratio. Community-based mobile test stations (cMTS) were used for conducting mass testing and treatment. Baseline (pre) and endline (post) household surveys were done in the control and intervention wards to assess the change in malaria prevalence measured by the interaction term of ‘time’ (post vs pre) and arm in a logistic model. A secondary analysis also studied the malaria incidence reported at the HFs during the intervention.ResultsOverall the 85 rounds of 1,7-mRCTR conducted in the intervention wards significantly reduced the odds of malaria infection by 66% (adjusted OR 0.34, 95%CI 0.26,0.44, p<0001) beyond the effect of the standard programmes. Malaria prevalence in the intervention wards declined by 81% (from 26% (95%CI, 23.7,7.8), at baseline to 4.9% (95%CI, 4.0,5.9) at endline). In villages receiving the 1,7-mRCTR, the short-term case ratio decreased by over 15.7% (95%CI, -33,6) compared to baseline.ConclusionThe 1,7-mRCTR approach significantly reduced the malaria burden in the areas of high transmission in rural southern Tanzania. This locally tailored approach could accelerate malaria control and elimination efforts. The results provide the impetus for further evaluation of the effectiveness and scaling up of this approach in other high malaria burden countries in Africa, including Tanzania.

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“…In Tanzania, a review of the most recent population-based malaria indicator survey and of health facility information has shown the high heterogeneity of malaria endemicity within regions across the country [11,[28][29][30][31], underscoring the need to carefully deploy appropriate interventions. New approaches for malaria control are needed to sustain and accelerate progress towards elimination, and the combination of the WHO-T3 initiative and the Chinese experience of surveillance and response offers a great opportunity for the identi cation of new approaches.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of The Innovative 1,7-Malaria Reactive Community-based Testing and Response (1, 7-mRCTR) Approach on Malaria Burden Reduction in Southeastern Tanzania

Mlacha

Wang²,

Chaki

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: In 2015, a China-UK-Tanzania tripartite pilot project was implemented in south-eastern Tanzania to explore a new model for reducing malaria burden and possibly scaling-out the approach into other malaria endemic countries. The 1,7-malaria Reactive Community-based Testing and Response (1,7-RCTR) which is a locally-tailored approach for reporting febrile malaria cases in endemic villages was developed to stop transmission and plasmodium life-cycle. The (1,7-RCTR) utilizes existing health facility data and locally trained community health workers to conduct community-level testing and treatment. Methods: The pilot project was implemented from September 2015 to June 2018. Matched malaria incidence pairs of control and intervention wards were chosen. The latter arm was selected for the 1,7-mRCTR approach leaving control wards relying on existed programs. The 1,7-mRCTR activities included community testing and treatment of malaria infection. Malaria case-to-suspect ratios at health facilities (HF) were aggregated by villages, weekly to identify the village with the highest ratio. Community-based mobile test stations (cMTS) were used for conducting mass testing and treatment. Random household surveys were done in the control and intervention wards before (baseline) and after (endline) the program. The primary outcome was the baseline and endline difference of malaria prevalence in the control and intervention wards measured by the interaction term of ‘time’ (post vs. pre) and group in a logistic model. We also studied the malaria incidence reported at the health facilities during the intervention.Results: Overall 85 rounds of 1,7-mRCT conducted in the intervention wards significantly reduced the odds of malaria infection by 66% (adjusted OR 0.34, 95%CI 0.26,0.44, p<0001) beyond the effect of the standard programs. Malaria prevalence in the intervention wards declined by 81% (from 26% (95% CI, 23.7, 7.8), at baseline to 4.9% (95% CI, 4.0,5.9) at endline). Villages receiving the 1,7-mRCT had a case ratio decreased by over 15.7% (95%CI, -33, 6) compared to baseline.Conclusion: The 1,7-mRCTR approach reduced significantly the malaria burden in the areas of moderate and high transmission in southern Tanzania. This locally-tailored approach could accelerate malaria control and elimination efforts. The results provide the impetus for further evaluation of the effectiveness and scaling up of this type of approach in other high malaria burden countries in Africa, including Tanzania.

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Simulating the council-specific impact of anti-malaria interventions: A tool to support malaria strategic planning in Tanzania

Abstract: Simulating the council-specific impact of antimalaria interventions: A tool to support malaria strategic planning in Tanzania. PLoS ONE 15(2): e0228469.

Cited by 30 publications

References 96 publications

Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

Effectiveness of the innovative 1,7-malaria reactive community-based testing and response (1, 7-mRCTR) approach on malaria burden reduction in Southeastern Tanzania

Effectiveness of The Innovative 1,7-Malaria Reactive Community-based Testing and Response (1, 7-mRCTR) Approach on Malaria Burden Reduction in Southeastern Tanzania

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