Malaria Risk Map Using Spatial Multi-Criteria Decision Analysis along Yunnan Border During the Pre-elimination Period

Xiao-min, Zhao; Thanapongtharm, Weerapong; Lawawirojwong, Siam; Wang, Chun; Tang, Yerong; Zhou, Yao-Wu; Sun, Xin; Sattabongkot, Jetsumon; Kaewkungwal, Jaranit

doi:10.4269/ajtmh.19-0854

Cited by 20 publications

(15 citation statements)

References 117 publications

(149 reference statements)

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“…This study nds a spatial variation of malaria cases between administrative wards. Similar results were reported in Mozambique [23,28,32] in Africa [33,34] and other parts of the World [35,36]. This study nds a decreasing tendency of malaria cases for age category 0 to 4 years.…”

Section: Discussionsupporting

confidence: 90%

Malaria Temporal Variation and Modelling Using Time-Series in Sussundenga District, Mozambique

Ferrão

Earland

Novela³

et al. 2020

Preprint

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Malaria is one of the leading causes of morbidity and mortality in Mozambique with the 5th highest prevalence in the world. Sussundenga district in Manica Province has documented high P. falciparum incidence at the local rural health center (RHC). Sussundenga is a rural district located along the Mozambique, Zimbabwe border. P. falciparum transmission in this area is unique as there are differing control policies on each side of the international border. The study objective was to analyze the P. falciparum temporal variation and model its pattern in Sussundenga district, Mozambique. Data from weekly epidemiological bulletins (BES) were collected from 2015 to 2019, which records confirmed P. falciparum cases from health facilities. These data categorize confirmed cases into two age groups: under 5 years and 5-years and older. P. falciparum incidence and temporal variation were calculated. Temporal clusters were identified using dendrograms. A time-series analysis was carried out. For temporal modeling a Box-Jenkins method was used applying an autoregressive integrated moving average (ARIMA). Over the study period, 372,498 cases of P. falciparum were recorded in Sussundenga, 177,957 from under 5 years (47.5 %) and 194,541 (52.2 %) from 5 years and older. There were weekly and yearly variations in incidence overall (p < 0.001). There was a decreasing trend in cases for those under 5 years while there was a slight increase in those 5 and older. For those under 5, week 2 of the year had the highest number of cases (1170 Sd 34 ) while week 35 had the fewest (354 Sd 17.8). For those 5-years and older, cases also peak at week 2 (1295 Sd 245) with week 31 having the fewest cases (341 Sd 193.5). The findings indicate that cases are decreasing in those under 5 years and are increasing slightly in those 5 years and over. The P. falciparum case occurrence presents a weekly temporal pattern peaking during the wet season. Based on the temporal distribution and using ARIMA modelling, more efficient strategies that target this seasonality can be implemented to reduce the overall malaria burden in Sussundenga District, and regionally.

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Section: Discussionsupporting

confidence: 90%

Malaria Temporal Variation and Modelling Using Time-Series in Sussundenga District, Mozambique

Ferrão

Earland

Novela³

et al. 2020

Preprint

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“…and China [ 30 ]. Rainfall increases the presence of stagnant water for malaria vectors for breeding and a weekly precipitation of over 10 mm will propitiate mosquito development [ 31 ]. Sussundenga has an average weekly precipitation of 22 m. from June to September the weekly precipitation is below 10 mm [ 10 ].…”

Section: Discussionmentioning

confidence: 99%

Mapping Risk of Malaria as a Function of Anthropic and Environmental Conditions in Sussundenga Village, Mozambique

Ferrão

Earland

Novela³

et al. 2021

IJERPH

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Mozambique is a country in Southern Africa with around 30 million inhabitants. Malaria is the leading cause of mortality in the country. According to the WHO, Mozambique has the third highest number of malaria cases in the world, representing approximately 5% of the world total cases. Sussundenga District has the highest incidence in the Manica province and environmental conditions are the major contributor to malaria transmission. There is a lack of malaria risk maps to inform transmission dynamics in Sussundenga village. This study develops a malaria risk map for Sussundenga Village in Mozambique and identifies high risk areas to inform on appropriate malaria control and eradication efforts. One hundred houses were randomly sampled and tested for malaria in Sussundenga Rural Municipality. To construct the map, a spatial conceptual model was used to estimate risk areas using ten environmental and anthropic factors. Data from Worldclim, 30 × 30 Landsat images were used, and layers were produced in a raster data set. Layers between class values were compared by assigning numerical values to the classes within each layer of the map with equal rank. Data set input was classified, using diverse weights depending on their appropriateness. The reclassified data outputs were combined after reclassification. The map indicated a high risk for malaria in the northeast and southeast, that is, the neighborhoods of Nhamazara, Nhamarenza, and Unidade. The central eastern areas, that is, 25 de Junho, 1 and 2, 7 de Abril, and Chicueu presented a moderate risk. In Sussundenga village there was 92% moderate and 8% high risk. High malaria risk areas are most often located in densely populated areas and areas close to water bodies. The relevant findings of this study can inform on effective malaria interventions.

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“…In the past several years, the malaria burden has been reduced in Kachin state due to cooperation between China and Myanmar regarding malaria elimination. However, the risk of malaria re-establishment in Chinese border areas should be of concern because malaria transmission still occurs on the Myanmar side 13 , 20 . Different cross-border activities may result in different temporal patterns of imported cases (e.g., the number of peak transmission seasons).…”

Section: Discussionmentioning

confidence: 99%

A retrospective analysis of malaria epidemiological characteristics in Yingjiang County on the China–Myanmar border

Huang

Li²,

Tian

et al. 2021

Sci Rep

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Yingjiang County, which is on the China–Myanmar border, is the main focus for malaria elimination in China. The epidemiological characteristics of malaria in Yingjiang County were analysed in a retrospective analysis. A total of 895 malaria cases were reported in Yingjiang County between 2013 and 2019. The majority of cases occurred in males (70.7%) and individuals aged 19–59 years (77.3%). Plasmodium vivax was the predominant species (96.6%). The number of indigenous cases decreased gradually and since 2017, no indigenous cases have been reported. Malaria cases were mainly distributed in the southern and southwestern areas of the county; 55.6% of the indigenous cases were reported in Nabang Township, which also had the highest risk of imported malaria. The “1–3–7” approach has been implemented effectively, with 100% of cases reported within 24 h, 88.9% cases investigated and confirmed within 3 days and 98.5% of foci responded to within 7 days. Although malaria elimination has been achieved in Yingjiang County, sustaining elimination and preventing the re-establishment of malaria require the continued strengthening of case detection, surveillance and response systems targeting the migrant population in border areas.

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Malaria Risk Map Using Spatial Multi-Criteria Decision Analysis along Yunnan Border During the Pre-elimination Period

Cited by 20 publications

References 117 publications

Malaria Temporal Variation and Modelling Using Time-Series in Sussundenga District, Mozambique

Malaria Temporal Variation and Modelling Using Time-Series in Sussundenga District, Mozambique

Mapping Risk of Malaria as a Function of Anthropic and Environmental Conditions in Sussundenga Village, Mozambique

A retrospective analysis of malaria epidemiological characteristics in Yingjiang County on the China–Myanmar border

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