Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016
Abstract Background Reliable measures of disease burden over time are necessary to evaluate the impact of interventions and assess sub-national trends in the distribution of infection. Three Malaria Indicator Surveys (MISs) have been conducted in Madagascar since 2011. They provide a valuable resour...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2018-05-01
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| Series: | BMC Medicine |
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| Online Access: | http://link.springer.com/article/10.1186/s12916-018-1060-4 |
| _version_ | 1828870857790849024 |
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| author | Su Yun Kang Katherine E. Battle Harry S. Gibson Arsène Ratsimbasoa Milijaona Randrianarivelojosia Stéphanie Ramboarina Peter A. Zimmerman Daniel J. Weiss Ewan Cameron Peter W. Gething Rosalind E. Howes |
| author_facet | Su Yun Kang Katherine E. Battle Harry S. Gibson Arsène Ratsimbasoa Milijaona Randrianarivelojosia Stéphanie Ramboarina Peter A. Zimmerman Daniel J. Weiss Ewan Cameron Peter W. Gething Rosalind E. Howes |
| author_sort | Su Yun Kang |
| collection | DOAJ |
| description | Abstract Background Reliable measures of disease burden over time are necessary to evaluate the impact of interventions and assess sub-national trends in the distribution of infection. Three Malaria Indicator Surveys (MISs) have been conducted in Madagascar since 2011. They provide a valuable resource to assess changes in burden that is complementary to the country’s routine case reporting system. Methods A Bayesian geostatistical spatio-temporal model was developed in an integrated nested Laplace approximation framework to map the prevalence of Plasmodium falciparum malaria infection among children from 6 to 59 months in age across Madagascar for 2011, 2013 and 2016 based on the MIS datasets. The model was informed by a suite of environmental and socio-demographic covariates known to influence infection prevalence. Spatio-temporal trends were quantified across the country. Results Despite a relatively small decrease between 2013 and 2016, the prevalence of malaria infection has increased substantially in all areas of Madagascar since 2011. In 2011, almost half (42.3%) of the country’s population lived in areas of very low malaria risk (<1% parasite prevalence), but by 2016, this had dropped to only 26.7% of the population. Meanwhile, the population in high transmission areas (prevalence >20%) increased from only 2.2% in 2011 to 9.2% in 2016. A comparison of the model-based estimates with the raw MIS results indicates there was an underestimation of the situation in 2016, since the raw figures likely associated with survey timings were delayed until after the peak transmission season. Conclusions Malaria remains an important health problem in Madagascar. The monthly and annual prevalence maps developed here provide a way to evaluate the magnitude of change over time, taking into account variability in survey input data. These methods can contribute to monitoring sub-national trends of malaria prevalence in Madagascar as the country aims for geographically progressive elimination. |
| first_indexed | 2024-12-13T06:20:38Z |
| format | Article |
| id | doaj.art-4760d7b752c340bc8e01253cacc58b7f |
| institution | Directory Open Access Journal |
| issn | 1741-7015 |
| language | English |
| last_indexed | 2024-12-13T06:20:38Z |
| publishDate | 2018-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medicine |
| spelling | doaj.art-4760d7b752c340bc8e01253cacc58b7f2022-12-21T23:56:51ZengBMCBMC Medicine1741-70152018-05-0116111510.1186/s12916-018-1060-4Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016Su Yun Kang0Katherine E. Battle1Harry S. Gibson2Arsène Ratsimbasoa3Milijaona Randrianarivelojosia4Stéphanie Ramboarina5Peter A. Zimmerman6Daniel J. Weiss7Ewan Cameron8Peter W. Gething9Rosalind E. Howes10Malaria Atlas Project, Oxford Big Data Institute, Nuffield Department of Medicine, University of OxfordMalaria Atlas Project, Oxford Big Data Institute, Nuffield Department of Medicine, University of OxfordMalaria Atlas Project, Oxford Big Data Institute, Nuffield Department of Medicine, University of OxfordNational Malaria Control Programme, Ministry of HealthInstitut Pasteur de MadagascarNational Malaria Control Programme, Ministry of HealthCenter for Global Health and Diseases, Case Western Reserve UniversityMalaria Atlas Project, Oxford Big Data Institute, Nuffield Department of Medicine, University of OxfordMalaria Atlas Project, Oxford Big Data Institute, Nuffield Department of Medicine, University of OxfordMalaria Atlas Project, Oxford Big Data Institute, Nuffield Department of Medicine, University of OxfordMalaria Atlas Project, Oxford Big Data Institute, Nuffield Department of Medicine, University of OxfordAbstract Background Reliable measures of disease burden over time are necessary to evaluate the impact of interventions and assess sub-national trends in the distribution of infection. Three Malaria Indicator Surveys (MISs) have been conducted in Madagascar since 2011. They provide a valuable resource to assess changes in burden that is complementary to the country’s routine case reporting system. Methods A Bayesian geostatistical spatio-temporal model was developed in an integrated nested Laplace approximation framework to map the prevalence of Plasmodium falciparum malaria infection among children from 6 to 59 months in age across Madagascar for 2011, 2013 and 2016 based on the MIS datasets. The model was informed by a suite of environmental and socio-demographic covariates known to influence infection prevalence. Spatio-temporal trends were quantified across the country. Results Despite a relatively small decrease between 2013 and 2016, the prevalence of malaria infection has increased substantially in all areas of Madagascar since 2011. In 2011, almost half (42.3%) of the country’s population lived in areas of very low malaria risk (<1% parasite prevalence), but by 2016, this had dropped to only 26.7% of the population. Meanwhile, the population in high transmission areas (prevalence >20%) increased from only 2.2% in 2011 to 9.2% in 2016. A comparison of the model-based estimates with the raw MIS results indicates there was an underestimation of the situation in 2016, since the raw figures likely associated with survey timings were delayed until after the peak transmission season. Conclusions Malaria remains an important health problem in Madagascar. The monthly and annual prevalence maps developed here provide a way to evaluate the magnitude of change over time, taking into account variability in survey input data. These methods can contribute to monitoring sub-national trends of malaria prevalence in Madagascar as the country aims for geographically progressive elimination.http://link.springer.com/article/10.1186/s12916-018-1060-4MadagascarPlasmodium falciparumGeostatistical modelMapMalaria Indicator Surveys |
| spellingShingle | Su Yun Kang Katherine E. Battle Harry S. Gibson Arsène Ratsimbasoa Milijaona Randrianarivelojosia Stéphanie Ramboarina Peter A. Zimmerman Daniel J. Weiss Ewan Cameron Peter W. Gething Rosalind E. Howes Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016 BMC Medicine Madagascar Plasmodium falciparum Geostatistical model Map Malaria Indicator Surveys |
| title | Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016 |
| title_full | Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016 |
| title_fullStr | Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016 |
| title_full_unstemmed | Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016 |
| title_short | Spatio-temporal mapping of Madagascar’s Malaria Indicator Survey results to assess Plasmodium falciparum endemicity trends between 2011 and 2016 |
| title_sort | spatio temporal mapping of madagascar s malaria indicator survey results to assess plasmodium falciparum endemicity trends between 2011 and 2016 |
| topic | Madagascar Plasmodium falciparum Geostatistical model Map Malaria Indicator Surveys |
| url | http://link.springer.com/article/10.1186/s12916-018-1060-4 |
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