Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon
Abstract Background In 2011, the demographic and health survey (DHS) in Cameroon was combined with the multiple indicator cluster survey. Malaria parasitological data were collected, but the survey period did not overlap with the high malaria transmission season. A malaria indicator survey (MIS) was...
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ftdoajarticles:oai:doaj.org/article:ac5360d7599f499e93f7808753947907 2023-05-15T15:18:05+02:00 Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon Salomon G. Massoda Tonye Celestin Kouambeng Romain Wounang Penelope Vounatsou 2018-04-01T00:00:00Z https://doi.org/10.1186/s12936-018-2284-7 https://doaj.org/article/ac5360d7599f499e93f7808753947907 EN eng BMC http://link.springer.com/article/10.1186/s12936-018-2284-7 https://doaj.org/toc/1475-2875 doi:10.1186/s12936-018-2284-7 1475-2875 https://doaj.org/article/ac5360d7599f499e93f7808753947907 Malaria Journal, Vol 17, Iss 1, Pp 1-14 (2018) Malaria Malaria indicator survey Demographic and health survey Parasitaemia Spatial correlation Malaria interventions Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2018 ftdoajarticles https://doi.org/10.1186/s12936-018-2284-7 2022-12-31T08:17:57Z Abstract Background In 2011, the demographic and health survey (DHS) in Cameroon was combined with the multiple indicator cluster survey. Malaria parasitological data were collected, but the survey period did not overlap with the high malaria transmission season. A malaria indicator survey (MIS) was also conducted during the same year, within the malaria peak transmission season. This study compares estimates of the geographical distribution of malaria parasite risk and of the effects of interventions obtained from the DHS and MIS survey data. Methods Bayesian geostatistical models were applied on DHS and MIS data to obtain georeferenced estimates of the malaria parasite prevalence and to assess the effects of interventions. Climatic predictors were retrieved from satellite sources. Geostatistical variable selection was used to identify the most important climatic predictors and indicators of malaria interventions. Results The overall observed malaria parasite risk among children was 33 and 30% in the DHS and MIS data, respectively. Both datasets identified the Normalized Difference Vegetation Index and the altitude as important predictors of the geographical distribution of the disease. However, MIS selected additional climatic factors as important disease predictors. The magnitude of the estimated malaria parasite risk at national level was similar in both surveys. Nevertheless, DHS estimates lower risk in the North and Coastal areas. MIS did not find any important intervention effects, although DHS revealed that the proportion of population with an insecticide-treated nets access in their household was statistically important. An important negative relationship between malaria parasitaemia and socioeconomic factors, such as the level of mother’s education, place of residence and the household welfare were captured by both surveys. Conclusion Timing of the malaria survey influences estimates of the geographical distribution of disease risk, especially in settings with seasonal transmission. In countries with ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 17 1 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
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English |
topic |
Malaria Malaria indicator survey Demographic and health survey Parasitaemia Spatial correlation Malaria interventions Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Malaria Malaria indicator survey Demographic and health survey Parasitaemia Spatial correlation Malaria interventions Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Salomon G. Massoda Tonye Celestin Kouambeng Romain Wounang Penelope Vounatsou Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon |
topic_facet |
Malaria Malaria indicator survey Demographic and health survey Parasitaemia Spatial correlation Malaria interventions Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background In 2011, the demographic and health survey (DHS) in Cameroon was combined with the multiple indicator cluster survey. Malaria parasitological data were collected, but the survey period did not overlap with the high malaria transmission season. A malaria indicator survey (MIS) was also conducted during the same year, within the malaria peak transmission season. This study compares estimates of the geographical distribution of malaria parasite risk and of the effects of interventions obtained from the DHS and MIS survey data. Methods Bayesian geostatistical models were applied on DHS and MIS data to obtain georeferenced estimates of the malaria parasite prevalence and to assess the effects of interventions. Climatic predictors were retrieved from satellite sources. Geostatistical variable selection was used to identify the most important climatic predictors and indicators of malaria interventions. Results The overall observed malaria parasite risk among children was 33 and 30% in the DHS and MIS data, respectively. Both datasets identified the Normalized Difference Vegetation Index and the altitude as important predictors of the geographical distribution of the disease. However, MIS selected additional climatic factors as important disease predictors. The magnitude of the estimated malaria parasite risk at national level was similar in both surveys. Nevertheless, DHS estimates lower risk in the North and Coastal areas. MIS did not find any important intervention effects, although DHS revealed that the proportion of population with an insecticide-treated nets access in their household was statistically important. An important negative relationship between malaria parasitaemia and socioeconomic factors, such as the level of mother’s education, place of residence and the household welfare were captured by both surveys. Conclusion Timing of the malaria survey influences estimates of the geographical distribution of disease risk, especially in settings with seasonal transmission. In countries with ... |
format |
Article in Journal/Newspaper |
author |
Salomon G. Massoda Tonye Celestin Kouambeng Romain Wounang Penelope Vounatsou |
author_facet |
Salomon G. Massoda Tonye Celestin Kouambeng Romain Wounang Penelope Vounatsou |
author_sort |
Salomon G. Massoda Tonye |
title |
Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon |
title_short |
Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon |
title_full |
Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon |
title_fullStr |
Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon |
title_full_unstemmed |
Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon |
title_sort |
challenges of dhs and mis to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of cameroon |
publisher |
BMC |
publishDate |
2018 |
url |
https://doi.org/10.1186/s12936-018-2284-7 https://doaj.org/article/ac5360d7599f499e93f7808753947907 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 17, Iss 1, Pp 1-14 (2018) |
op_relation |
http://link.springer.com/article/10.1186/s12936-018-2284-7 https://doaj.org/toc/1475-2875 doi:10.1186/s12936-018-2284-7 1475-2875 https://doaj.org/article/ac5360d7599f499e93f7808753947907 |
op_doi |
https://doi.org/10.1186/s12936-018-2284-7 |
container_title |
Malaria Journal |
container_volume |
17 |
container_issue |
1 |
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1766348319986024448 |