Jinsi tunavyosaidia mapambano dhidi ya malaria

Kila kitu MAP hufanya kinalenga kufikia athari. Hii hutokea tu kwa kushirikiana na wale wanaofanya maamuzi ambayo ni muhimu, ikiwa ni pamoja na watunga sera za malaria, wafadhili na wafanyakazi wa programu ya udhibiti.

Athari zetu

Tunachofanya

MAP is dedicated to driving positive impact in malaria policy, funding decisions, scientific research and capacity strengthening. We prioritize research excellence in generating analytical insights that accelerate progress towards malaria eradication.

Our pioneering global map of Plasmodium falciparum malaria endemicity has served as a crucial resource for global malaria strategy and policy formulation, national program implementation, and monitoring efforts. For years, we have maintained the largest and most comprehensive malaria data repository which provides core malaria analytics such as malaria burden and intervention coverage and cause-specific mortality estimation, to World Health Organization’s annual World Malaria Report. MAP’s analytical insights also guide decisions on RTSS vaccine prioritisation, the Global Fund’s allocation and replenishment decisions across diseases and countries, and inform progress, projections, and advocacy for investment cases. We are also key contributors to the Institute of Health Metrics’ Global Burden of Disease study.

Our estimates and model outputs are used by a range of downstream stakeholders including intergovernmental organizations, funding and implementing partners, modeling groups and research organizations. Notable examples include contributions to the World Bank’s global database, ALMA’s scorecard, Malaria No More Commonwealth Dashboard and the President’s Malaria Initiative annual performance monitoring and reporting to congress

MAP’s role in creating robust evidence for national malaria policy and decision-making is further strengthened by presence on the African continent, where we provide tailored, timely support to 40 malaria-endemic countries. This support is closely integrated with efforts to strengthen research leadership in geospatial malaria modelling to ensure sustained impact.

Taswira

Machapisho

Evaluating COVID-19-Related Disruptions to Effective Malaria Case Management in 2020–2021 and Its…

published 05 April 2023
Authors: Paulina A. Dzianach et al

Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and…

published 21 September 2020
Authors: Daniel J Weiss et al

Maps and metrics of insecticide-treated net access, use, and nets-per-capita in Africa…

published 11 June 2021
Authors: Amelia Bertozzi-Villa et al

Mapping the global endemicity and clinical burden of Plasmodium vivax, 2000–17: a…

published 19 June 2019
Authors: Katherine E Battle et al

Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum, 2000–17: a…

published 19 June 2019
Authors: Daniel J Weiss et al

Plasmodium falciparum Mortality in Africa between 1990 and 2015

published 21 June 2017
Authors: N/A

Machapisho ya Watafiti

The dominant Anopheles vectors of human malaria in Africa, Europe and the…

published 03 December 2010
Authors: Marianne E Sinka et al

The dominant Anopheles vectors of human malaria in the Americas: occurrence data,…

published 17 August 2010
Authors: Marianne E Sinka et al

The International Limits and Population at Risk of Plasmodium vivax Transmission in…

published 03 August 2010
Authors: Carlos A. Guerra et al

Ramani ya malaria duniani: Plasmodium falciparum Endemicity mwaka 2007

published 19 March 2009
Authors: Simon I Hay et al

Defining the relationship between Plasmodium falciparum parasite rate and clinical disease: statistical…

published 05 August 2009
Authors: Anand P Patil et al

Spatial Predictions of Rhodesian Human African Trypanosomiasis (Sleeping Sickness) Prevalence in Kaberamaido…

published 14 December 2009
Authors: Nicola A. Batchelor et al

Hatari ya maambukizi ya malaria nchini Kenya mwaka 2009

published 23 November 2009
Authors: Abdisalan M Noor et al

Developing Geostatistical Space–Time Models to Predict Outpatient Treatment Burdens from Incomplete National…

published 18 March 2008
Authors: Peter W. Gething et al

A local space–time kriging approach applied to a national outpatient malaria data…

published 14 June 2007
Authors: P.W. Gething et al

Information for decision making from imperfect national data: tracking major changes in…

published 11 December 2007
Authors: Peter W Gething et al

Improving Imperfect Data from Health Management Information Systems in Africa Using Space–Time…

published 23 May 2006
Authors: Peter W Gething et al

Empirical modelling of government health service use by children with fevers in…

published 22 June 2004
Authors: Peter W. Gething et al
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