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

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.

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Spatial-temporal Distribution and Demography of Knowlesi Malaria in Peninsular Malaysia, 2011 to 2018

10.21203/rs.3.rs-34666/v1 ◽

2020 ◽

Author(s):

Wei Kit Phang ◽

Mohd Hafizi bin Abdul Hamid ◽

Jenarun Jelip ◽

Rose Nani binti Mudin ◽

Ting-Wu Chuang ◽

...

Keyword(s):

Spatial Clustering ◽

Plasmodium Knowlesi ◽

Malaria Incidence ◽

Temporal Distribution ◽

Northern Region ◽

Peninsular Malaysia ◽

Spatial And Temporal Patterns ◽

Zoonotic Malaria ◽

Global And Local ◽

Epidemiological Characteristics

Abstract Background: The life-threatening zoonotic malaria caused by Plasmodium knowlesi is on the rise in Malaysia; however, previous studies mainly focus on the transmission in Malaysian Borneo. This study aims to describe the basic epidemiological characteristics of P. knowlesi infection and identify spatial clustering of knowlesi malaria in Peninsular Malaysia. Methods : The spatial distribution of P. knowlesi monoinfection incidence was mapped across Peninsular Malaysia using Geographic Information System (GIS) approach. Demographic characteristics of the infection was investigated. Global and Local Moran’s I were used to analyze spatial autocorrelation and define clustering of knowlesi malaria incidence. Results : Gua Musang and Lipis maintained the highest incidence rate (IR) as compared to other districts. Spatial analysis revealed that high IRs (hotspots) were clustered in the central-northern region of Peninsular Malaysia. In the demographic aspect, knowlesi malaria was more prevalent in male and age between 20 and 39. Conclusions : This study revealed the spatial and temporal patterns of P. knowlesi in Peninsular Malaysia throughout 2011 to 2018. Knowlesi malaria control strategy should be emphasized in Malaysia malaria eradication program.

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Klasifikasi Wilayah Provinsi Aceh Berdasarkan Tingkat Kerentanan Kasus Malaria Tahun 2015 – 2018

JURNAL KESEHATAN LINGKUNGAN INDONESIA ◽

10.14710/jkli.18.1.25-33 ◽

2019 ◽

Vol 18 (1) ◽

pp. 25

Author(s):

Aja Fatimah Zohra ◽

Samsul Anwar ◽

Aida Fitri ◽

Muhammad Haikal Nasution

Keyword(s):

World Health Organization ◽

Plasmodium Vivax ◽

Malaria Elimination ◽

Plasmodium Knowlesi ◽

Malaria Incidence ◽

World Health ◽

Whitney Test ◽

Mann Whitney Test ◽

Aceh Province ◽

Health Organization

Latar belakang: Malaria merupakan salah satu kasus penyakit yang tidak pernah hilang. World Health Organization (WHO) memperkirakan sebanyak 300 hingga 500 juta orang terinfeksi malaria tiap tahunnya dengan angka kematian berkisar antara 1,5 hingga 2,7 juta pertahun. Pemerintah melalui Rencana Pembangunan Jangka Menengah Nasional (RPJMN) tahun 2015-2019 menargetkan sebanyak 300 kabupaten/kota akan memiliki sertifikasi eliminasi malaria pada tahun 2019. Penelitian ini merupakan penelitian pendahuluan terkait dengan distribusi dan prevalensi kejadian malaria di Provinsi Aceh. Meskipun sebagian besar kabupaten/kota di Provinsi Aceh sudah memiliki sertifikat eliminasi malaria, akan tetapi sebagian wilayah masih terdapat kasus malaria yang relatif tinggi. Penelitian ini bertujuan untuk mengetahui jenis parasit plasmodium yang paling dominan menyebabkan penyakit malaria dan mengklasifikasikan wilayah Provinsi Aceh yang rentan terserang kasus malaria berdasarkan indikator Annual Parasite Incidence (API).Metode: Penelitian ini adalah penelitian analitik kuantitatif dengan pendekatan data panel. Sampel pada penelitian ini adalah kasus malaria yang terjadi di 23 kabupaten/kota di Provinsi Aceh dari tahun 2015 sampai 2018 yang bersumber dari Dinas Kesehatan Provinsi Aceh. Metode statistik yang digunakan adalah analisis non-parametrik Kruskal-Wallis test, Mann-Whitney test dan K-Means Clustering. Hasil: Terdapat tiga jenis parasit yang paling dominan menyebabkan kasus malaria di Provinsi Aceh yaitu plasmodium vivax, plasmodium falcifarum dan plasmodium knowlesi. Berdasarkan indikator Annual Parasite Incidence (API), metode K-means clustering menunjukkan bahwa Kabupaten Aceh Jaya, Kota Sabang dan Kabupaten Aceh Selatan merupakan tiga wilayah yang paling rentan untuk terserang kasus malaria di Provinsi Aceh.Simpulan: Jenis-jenis parasit penyebab kasus malaria tertinggi adalah plasmodium vivax, plasmodium falcifarum dan plasmodium knowlesi. Tiga wilayah di Provinsi Aceh yang paling rentan terserang kasus malaria berdasarkan indikator API adalah Kabupaten Aceh Jaya, Kota Sabang dan Kabupaten Aceh Selatan.ABSTRACTTitle: Classification of Aceh Province Region Based on Vulnerability Levels of Malaria Cases in 2015 - 2018Background: Malaria is a case of an emerging disease. World Health Organization (WHO) estimates that 300 to 500 million people are infected with malaria each year with mortality rate ranging from 1.5 to 2.7 million per year. The government through the National Medium Term Development Plan (RPJMN) for 2015-2019 targets as many as 300 districts/cities to have certification of malaria elimination in 2019. This is a preliminary study related to the distribution and prevalence of malaria incidence in Aceh Province. Although most districts/cities in Aceh Province have been awarded malaria elimination certificates, some regions still have relatively high cases of malaria. This study aims to determine the type of plasmodium parasite that is the most dominant cause of malaria and to classify the regions in Aceh Province that is vulnerable to malaria cases based on the Annual Parasite Incidence (API) indicator.Method: This study is a quantitative analytical research study with panel data approach. The sample in this study was malaria cases that occurred in 23 districts/cities in Aceh Province from 2015 to 2018 obtained from the Aceh Provincial Health Office. The statistical methods used in this study were the non-parametric Kruskal-Wallis test, Mann-Whitney test and K-Means Clustering analyses.Result: There are three types of parasites which are the most dominant causes of malaria cases in Aceh Province, namely plasmodium vivax, plasmodium falcifarum and plasmodium knowlesi. Based on the Annual Parasite Incidence (API) indicator, the K-means clustering method shows that Aceh Jaya District, Sabang City and South Aceh District are the three most vulnerable areas for malaria in Aceh Province.Conclusion: The types of parasites that cause the highest malaria cases are plasmodium vivax, plasmodium falcifarum and plasmodium knowlesi. Three regions in Aceh Province that are most vulnerable to malaria cases based on API indicator are Aceh Jaya District, Sabang City and South Aceh District.

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Malaria elimination in Malaysia and the rising threat of Plasmodium knowlesi

Journal of PHYSIOLOGICAL ANTHROPOLOGY ◽

10.1186/s40101-020-00247-5 ◽

2020 ◽

Vol 39 (1) ◽

Author(s):

Abraham Zefong Chin ◽

Marilyn Charlene Montini Maluda ◽

Jenarun Jelip ◽

Muhammad Saffree Bin Jeffree ◽

Richard Culleton ◽

...

Keyword(s):

Public Health ◽

Health Problem ◽

Malaria Elimination ◽

Plasmodium Knowlesi ◽

Public Health Problem ◽

Strategic Plan ◽

World Health ◽

Major Public Health Problem ◽

Human Malaria ◽

Zoonotic Malaria

Abstract Background Malaria is a major public-health problem, with over 40% of the world’s population (more than 3.3 billion people) at risk from the disease. Malaysia has committed to eliminate indigenous human malaria transmission by 2020. The objective of this descriptive study is to understand the epidemiology of malaria in Malaysia from 2000 through 2018 and to highlight the threat posed by zoonotic malaria to the National Malaria Elimination Strategic Plan. Methods Malaria is a notifiable infection in Malaysia. The data used in this study were extracted from the Disease Control Division, Ministry of Health Malaysia, contributed by the hospitals and health clinics throughout Malaysia. The population data used in this study was extracted from the Department of Statistics Malaysia. Data analyses were performed using Microsoft Excel. Data used for mapping are available at EPSG:4326 WGS84 CRS (Coordinate Reference System). Shapefile was obtained from igismap. Mapping and plotting of the map were performed using QGIS. Results Between 2000 and 2007, human malaria contributed 100% of reported malaria and 18–46 deaths per year in Malaysia. Between 2008 and 2017, indigenous malaria cases decreased from 6071 to 85 (98.6% reduction), while during the same period, zoonotic Plasmodium knowlesi cases increased from 376 to 3614 cases (an 861% increase). The year 2018 marked the first year that Malaysia did not report any indigenous cases of malaria caused by human malaria parasites. However, there was an increasing trend of P. knowlesi cases, with a total of 4131 cases reported in that year. Although the increased incidence of P. knowlesi cases can be attributed to various factors including improved diagnostic capacity, reduction in human malaria cases, and increase in awareness of P. knowlesi, more than 50% of P. knowlesi cases were associated with agriculture and plantation activities, with a large remainder proportion linked to forest-related activities. Conclusions Malaysia has entered the elimination phase of malaria control. Zoonotic malaria, however, is increasing exponentially and becoming a significant public health problem. Improved inter-sectoral collaboration is required in order to develop a more integrated effort to control zoonotic malaria. Local political commitment and the provision of technical support from the World Health Organization will help to create focused and concerted efforts towards ensuring the success of the National Malaria Elimination Strategic Plan.

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Non-human primate and human malaria: past, present and future

Journal of Travel Medicine ◽

10.1093/jtm/taab036 ◽

2021 ◽

Author(s):

Spinello Antinori ◽

Cecilia Bonazzetti ◽

Andrea Giacomelli ◽

Mario Corbellino ◽

Massimo Galli ◽

...

Keyword(s):

Plasmodium Knowlesi ◽

Plasmodium Species ◽

Molecular Techniques ◽

Malaria Parasites ◽

Human Malaria ◽

Complex Interactions ◽

Zoonotic Malaria ◽

The Impact ◽

Human Plasmodium ◽

Human Primate

Abstract Background Studies of the malaria parasites infecting various non-human primates (NHPs) have increased our understanding of the origin, biology and pathogenesis of human Plasmodium parasites. This review considers the major discoveries concerning NHP malaria parasites, highlights their relationships with human malaria and considers the impact that this may have on attempts to eradicate the disease. Results The first description of NHP malaria parasites dates back to the early 20th century. Subsequently, experimental and fortuitous findings indicating that some NHP malaria parasites can be transmitted to humans have raised concerns about the possible impact of a zoonotic malaria reservoir on efforts to control human malaria. Advances in molecular techniques over the last 15 years have contributed greatly to our knowledge of the existence and geographical distribution of numerous Plasmodium species infecting NHPs, and extended our understanding of their close phylogenetic relationships with human malaria parasites. The clinical application of such techniques has also made it possible to document ongoing spillovers of NHP malaria parasites (Plasmodium knowlesi, P. cynomolgi, P. simium, P. brasilianum) in humans living in or near the forests of Asia and South America, thus confirming that zoonotic malaria can undermine efforts to eradicate human malaria. Conclusions Increasing molecular research supports the prophetic intuition of the pioneers of modern malariology who saw zoonotic malaria as a potential obstacle to the full success of malaria eradication programmes. It is, therefore, important to continue surveillance and research based on one-health approaches in order to improve our understanding of the complex interactions between NHPs, mosquito vectors and humans during a period of ongoing changes in the climate and the use of land, monitor the evolution of zoonotic malaria, identify the populations most at risk and implement appropriate preventive strategies.

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Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps

Advances in Meteorology ◽

10.1155/2017/8576150 ◽

2017 ◽

Vol 2017 ◽

pp. 1-11 ◽

Cited By ~ 9

Author(s):

Adeoluwa Akande ◽

Ana Cristina Costa ◽

Jorge Mateu ◽

Roberto Henriques

Keyword(s):

Extreme Precipitation ◽

Large Scale ◽

Northern Region ◽

Extreme Weather Events ◽

Self Organizing Map ◽

Spatial And Temporal Patterns ◽

Self Organizing Maps ◽

The North ◽

Precipitation Regimes ◽

Self Organizing

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

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Spatiotemporal distributed lag modelling of multiple Plasmodium species in a malaria elimination setting

Statistical Methods in Medical Research ◽

10.1177/0962280220938977 ◽

2021 ◽

Vol 30 (1) ◽

pp. 22-34

Author(s):

Chawarat Rotejanaprasert ◽

Duncan Lee ◽

Nattwut Ekapirat ◽

Prayuth Sudathip ◽

Richard J Maude

Keyword(s):

Data Streams ◽

Malaria Elimination ◽

Parasite Species ◽

Climatic Factors ◽

Plasmodium Species ◽

Clinical Malaria ◽

Spatiotemporal Patterns ◽

Distributed Lag ◽

Multiple Data

In much of the Greater Mekong Sub-region, malaria is now confined to patches and small foci of transmission. Malaria transmission is seasonal with the spatiotemporal patterns being associated with variation in environmental and climatic factors. However, the possible effect at different lag periods between meteorological variables and clinical malaria has not been well studied in the region. Thus, in this study we developed distributed lagged modelling accounting for spatiotemporal excessive zero cases in a malaria elimination setting. A multivariate framework was also extended to incorporate multiple data streams and investigate the spatiotemporal patterns from multiple parasite species via their lagged association with climatic variables. A simulation study was conducted to examine robustness of the methodology and a case study is provided of weekly data of clinical malaria cases at sub-district level in Thailand.

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Plasmodium knowlesi: An Important Yet Overlooked Human Malaria Parasite

Mayo Clinic Proceedings ◽

10.1016/s0025-6196(11)60759-3 ◽

2009 ◽

Vol 84 (7) ◽

pp. 664

Author(s):

Balaji Yegneswaran ◽

David Alcid ◽

Janani Mohan

Keyword(s):

Malaria Parasite ◽

Plasmodium Knowlesi ◽

Human Malaria Parasite ◽

Human Malaria

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Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

The Open Infectious Diseases Journal ◽

10.2174/1874279301810010088 ◽

2018 ◽

Vol 10 (1) ◽

pp. 88-100 ◽

Cited By ~ 5

Author(s):

Gbenga J. Abiodun ◽

Peter J. Witbooi ◽

Kazeem O. Okosun ◽

Rajendra Maharaj

Keyword(s):

Climate Variability ◽

Malaria Transmission ◽

Malaria Incidence ◽

Principal Component ◽

Wavelet Coherence ◽

Human Malaria ◽

Kwazulu Natal ◽

The Impact ◽

Wavelet Coherence Analysis ◽

Malaria Model

Introduction: The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas. Methods: In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence. Results: Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

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Micro-Stratification for Malaria Transmission Risk in a High Burden Area of Honduras

10.21203/rs.3.rs-418870/v1 ◽

2021 ◽

Author(s):

José Orlinder Nicolas ◽

Denis Escobar ◽

Engels Banegas ◽

José Ramón Valdez ◽

Rosa Elena Mejía Torres ◽

...

Keyword(s):

Malaria Elimination ◽

Malaria Incidence ◽

Epidemiological Data ◽

Transmission Risk ◽

Who Guidelines ◽

Demographic Information ◽

Health System Improvement ◽

System Improvement ◽

Endemic Areas ◽

Elimination Goal

Abstract Background As Malaria cases are continuously reported across the globe, epidemiological and integral approaches should be considered for an optimal stratification on endemic areas for elimination goal. In Central America, a 75% reduction in malaria incidence has been reported between 2000 and 2015, similarly, in Honduras, more than 75% of total cases in 2016 were concentrated in 7 municipalities, mainly in Gracias Dios department. Achieve malaria elimination in Honduras demands the implementation of strategies to identify main hotspots. Methods Based on WHO guidelines, local malaria epidemiological data from case-based surveillance system of the Ministry of Health between January and December 2016 were analysed. Furthermore, on field evaluations were carried out in Puerto Lempira municipality, Gracias a Dios department to an analysis validation. Finally, a set of epidemiological components were generated and proposed together with risk-factor description and proposed actions for health system improvement. Results On 2016, Gracias a Dios reported 61% of total malaria cases in Honduras; based on our analysis, 12 micro-areas were identified, including epidemiological, entomological, and socio-demographic information from local technicians. Conclusions Malaria elimination in endemic areas urges implementation of different strategies, here we show the on-field micro-stratification process of 12 “micro-areas” carried out in one endemic department of Honduras. This information provides a more targeted strategy for diagnosis, treatment, and vector control interventions for malaria elimination goal in Honduras.

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