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Spatial and Temporal Patterns of Plasmodium knowlesi Malaria in Sarawak from 2008 to 2017.

ABSTRACT: Zoonotic knowlesi malaria has replaced human malaria as the most prevalent malaria disease in Malaysia. The persistence of knowlesi malaria in high-risk transmission areas or hotspots can be discouraging to existing malaria elimination efforts. In this study, retrospective data of laboratory-confirmed knowlesi malaria cases were obtained from the Sarawak Health Department to investigate the spatiotemporal patterns and clustering of knowlesi malaria in the state of Sarawak from 2008 to 2017. Purely spatial, purely temporal, and spatiotemporal analyses were performed using SaTScan software to define clustering of knowlesi malaria incidence. Purely spatial and spatiotemporal analyses indicated most likely clusters of knowlesi malaria in the northern region of Sarawak, along the Sarawak-Kalimantan border, and the inner central region of Sarawak between 2008 and 2017. Temporal cluster was detected between September 2016 and December 2017. This study provides evidence of the existence of statistically significant Plasmodium knowlesi malaria clusters in Sarawak, Malaysia. The analysis approach applied in this study showed potential in establishing surveillance and risk management system for knowlesi malaria control as Malaysia approaches human malaria elimination.

SUBMITTER: Ooi CH

PROVIDER: S-EPMC8103491 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Spatial and Temporal Patterns of Plasmodium knowlesi Malaria in Sarawak from 2008 to 2017.

Ooi Choo Huck CH Phang Wei Kit WK Kent Liew Jonathan Wee JW Lau Yee Ling YL

The American journal of tropical medicine and hygiene 20210322 5

Zoonotic knowlesi malaria has replaced human malaria as the most prevalent malaria disease in Malaysia. The persistence of knowlesi malaria in high-risk transmission areas or hotspots can be discouraging to existing malaria elimination efforts. In this study, retrospective data of laboratory-confirmed knowlesi malaria cases were obtained from the Sarawak Health Department to investigate the spatiotemporal patterns and clustering of knowlesi malaria in the state of Sarawak from 2008 to 2017. Pure ...[more]

PMID: 33755585

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Project description:BackgroundPlasmodium knowlesi is a significant cause of human malaria in Sarawak, Malaysian Borneo. Only one study has been previously undertaken in Sarawak to identify vectors of P. knowlesi, where Anopheles latens was incriminated as the vector in Kapit, central Sarawak. A study was therefore undertaken to identify malaria vectors in a different location in Sarawak.MethodsMosquitoes found landing on humans and resting on leaves over a 5-day period at two sites in the Lawas District of northern Sarawak were collected and identified. DNA samples extracted from salivary glands of Anopheles mosquitoes were subjected to nested PCR malaria-detection assays. The small subunit ribosomal RNA (SSU rRNA) gene of Plasmodium was sequenced, and the internal transcribed spacer 2 (ITS2) and mitochondrial cytochrome c oxidase subunit 1 (cox1) gene of the mosquitoes were sequenced from the Plasmodium-positive samples for phylogenetic analysis.ResultsTotals of 65 anophelines and 127 culicines were collected. By PCR, 6 An. balabacensis and 5 An. donaldi were found to have single P. knowlesi infections while 3 other An. balabacensis had either single, double or triple infections with P. inui, P. fieldi, P. cynomolgi and P. knowlesi. Phylogenetic analysis of the Plasmodium SSU rRNA gene confirmed 3 An. donaldi and 3 An. balabacensis with single P. knowlesi infections, while 3 other An. balabacensis had two or more Plasmodium species of P. inui, P. knowlesi, P. cynomolgi and some species of Plasmodium that could not be conclusively identified. Phylogenies inferred from the ITS2 and/or cox1 sequences of An. balabacensis and An. donaldi indicate that they are genetically indistinguishable from An. balabacensis and An. donaldi, respectively, found in Sabah, Malaysian Borneo.ConclusionsPreviously An. latens was identified as the vector for P. knowlesi in Kapit, central Sarawak, Malaysian Borneo, and now An. balabacensis and An. donaldi have been incriminated as vectors for zoonotic malaria in Lawas, northern Sarawak.

Project description:BackgroundThe objective of this study is to analyze the spatial and temporal patterns of malaria incidence as to determine the means by which climatic factors such as temperature, rainfall and humidity affect its distribution in Maputo province, Mozambique.MethodsThis study presents a model of malaria that evolves in space and time in Maputo province-Mozambique, over a ten years period (1999-2008). The model incorporates malaria cases and their relation to environmental variables. Due to incompleteness of climatic data, a multiple imputation technique is employed. Additionally, the whole province is interpolated through a Gaussian process. This method overcomes the misalignment problem of environmental variables (available at meteorological stations--points) and malaria cases (available as aggregates for every district--area). Markov Chain Monte Carlo (MCMC) methods are used to obtain posterior inference and Deviance Information Criteria (DIC) to perform model comparison.ResultsA Bayesian model with interaction terms was found to be the best fitted model. Malaria incidence was associated to humidity and maximum temperature. Malaria risk increased with maximum temperature over 28 °C (relative risk (RR) of 0.0060 and 95% Bayesian credible interval (CI) of 0.00033-0.0095) and humidity (relative risk (RR) of 0.00741 and 95% Bayesian CI 0.005141-0.0093). The results would suggest that additional non-climatic factors including socio-economic status, elevation, etc. also influence malaria transmission in Mozambique.ConclusionsThese results demonstrate the potential of climate predictors particularly, humidity and maximum temperature in explaining malaria incidence risk for the studied period in Maputo province. Smoothed maps obtained as monthly average of malaria incidence allowed to visualize months of initial and peak transmission. They also illustrate a variation on malaria incidence risk that might not be related to climatic factors. However, these factors are still determinant for malaria transmission and intensity in the region.

Project description:BackgroundPlasmodium knowlesi, a simian malaria parasite infection, increases as Plasmodium falciparum and Plasmodium vivax infections decrease in Johor, Malaysia. Therefore, this study aimed to identify the distribution of vectors involved in knowlesi malaria transmission in Johor. This finding is vital in estimating hotspot areas for targeted control strategies.MethodsAnopheles mosquitoes were collected from the location where P. knowlesi cases were reported. Cases of knowlesi malaria from 2011 to 2019 in Johor were analyzed. Internal transcribed spacers 2 (ITS2) and cytochrome c oxidase subunit I (COI) genes were used to identify the Leucosphyrus Group of Anopheles mosquitoes. In addition, spatial analysis was carried out on the knowlesi cases and vectors in Johor.ResultsOne hundred and eighty-nine cases of P. knowlesi were reported in Johor over 10 years. Young adults between the ages of 20-39 years comprised 65% of the cases. Most infected individuals were involved in agriculture and army-related occupations (22% and 32%, respectively). Four hundred and eighteen Leucosphyrus Group Anopheles mosquitoes were captured during the study. Anopheles introlatus was the predominant species, followed by Anopheles latens. Spatial analysis by Kriging interpolation found that hotspot regions of P. knowlesi overlapped or were close to the areas where An. introlatus and An. latens were found. A significantly high number of vectors and P. knowlesi cases were found near the road within 0-5 km.ConclusionsThis study describes the distribution of P. knowlesi cases and Anopheles species in malaria-endemic transmission areas in Johor. Geospatial analysis is a valuable tool for studying the relationship between vectors and P. knowlesi cases. This study further supports that the Leucosphyrus Group of mosquitoes might be involved in transmitting knowlesi malaria cases in Johor. These findings may provide initial evidence to prioritize diseases and vector surveillance.

Dataset Information

Spatial and Temporal Patterns of Plasmodium knowlesi Malaria in Sarawak from 2008 to 2017.

Publications

Spatial and Temporal Patterns of Plasmodium knowlesi Malaria in Sarawak from 2008 to 2017.

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