Risk factor of plasmodium knowlesi infection in Sabah Borneo Malaysia, 2020: A population-based case-control study

Forest Restoration and the Zoonotic Vector Anopheles balabacensis in Sabah, Malaysia

Anthropogenic changes to forest cover have been linked to an increase in zoonotic diseases. In many areas, natural forests are being replaced with monoculture plantations, such as oil palm, which reduce biodiversity and create a mosaic of landscapes with increased forest edge habitat and an altered micro-climate. These altered conditions may be facilitating the spread of the zoonotic malaria parasite Plasmodium knowlesi in Sabah, on the island of Borneo, through changes to mosquito vector habitat. We conducted a study on mosquito abundance and diversity in four different land uses comprising restored native forest, degraded native forest, an oil palm estate and a eucalyptus plantation, these land uses varying in their vegetation types and structure. The main mosquito vector, Anopheles balabacensis, has adapted its habitat preference from closed canopy rainforest to more open logged forest and plantations. The eucalyptus plantations (Eucalyptus pellita) assessed in this study contained significantly higher abundance of many mosquito species compared with the other land uses, whereas the restored dipterocarp forest had a low abundance of all mosquitos, in particular, An. balabacensis. No P. knowlesi was detected by PCR assay in any of the vectors collected during the study; however, P. inui, P. fieldi and P. vivax were detected in An. balabacensis. These findings indicate that restoring degraded natural forests with native species to closed canopy conditions reduces abundance of this zoonotic malarial mosquito vector and therefore should be incorporated into future restoration research and potentially contribute to the control strategies against simian malaria.

Risk factors of malaria transmission in mining workers in Muara Enim, South Sumatra, Indonesia

Eliminating malaria by 2030 is stated as goal three in the UN's Sustainable Development Goals (SDGs). However, malaria still remains a significant public health problem. This study aims to identify the factors determining malaria transmission in artisanal or small-scale miner (ASM) communities in three villages: Tanjung Agung, Tanjung Lalang, and Penyandingan, located in the Tanjung Enim District, Muara Enim, South Sumatra, Indonesia. Researchers conducted a cross-sectional study involving 92 participants from the study area. They used a logistic regression model to investigate the risk factors related to malaria occurrence. The multivariable analysis revealed that age (Adjusted Prevalence Ratio (APR) = 7.989 with 95% CI 1.724-37.002) and mosquito breeding (APR = 7.685 with 95% CI 1.502-39.309) were risk factors for malaria. On the other hand, higher education (APR = 0.104 with 95% CI 0.027-0.403), the use of mosquito repellent (APR = 0.138 with 95% CI 0.035-0.549), and the condition of house walls (APR = 0.145 with 95% CI 0.0414-0.511) were identified as protective factors. The current study highlights age and mosquito breeding sites as risk factors for malaria. Additionally, higher education, insect repellent use, and the condition of house walls are protective factors against malaria. Therefore, reducing risk factors and increasing protective measures through effective communication, information, and education are highly recommended to eliminate malaria in mining areas.

Environmental determinants and risk behaviour in the case of indigenous malaria in Muara Enim Regency, Indonesia: A case-control design

INTRODUCTION

Malaria is a significant public health concern in Indonesia. Muara Enim Regency is one of the districts in South Sumatra with the most important number of indigenous malaria cases in the last three years (2018-2020). Therefore, this study aimed to identify determinants of indigenous malaria in the Muara Enim Regency.

METHODS

This study was designed as a case-control study. A stratified random sample in 2018, 2019, and 2020 was used at the Primary Health Centres (PHCs) areas of Tanjung Enim and Tanjung Agung. The sample included 49 cases and 49 controls. Indigenous malaria determinants were discovered using both bivariable and multivariable logistic regression models.

RESULT

The multivariable logistic regression model results show that mosquito repellent reduces malaria risk by 71% (AOR = 0.29, 95% CI: 0.11-0.64). Besides, the presence of wire mesh on ventilation reduces the risk of malaria by 76% (AOR = 0.24, 95% CI: 0.10-0.57), and the distance from mosquito breeding sites near hundred meters and fewer increases the risk of malaria by 3.88 fold (AOR = 3.88; 95% CI: 1.67-8.97).

CONCLUSIONS

Multivariable analysis revealed distance from mosquito breeding sites as a risk factor for malaria. Besides, the study shows that using insect repellent, wire netting in ventilation, eliminating mosquito breeding sites, mosquito repellent or protective clothing, and improving house conditions were protective factors for indigenous malaria. Therefore, preventive and promotional efforts are essential as the first step toward malaria elimination at the study site, including avoiding direct contact between residents and vectors near mosquito breeding sites.

High transmission efficiency of the simian malaria vectors and population expansion of their parasites Plasmodium cynomolgi and Plasmodium inui

BACKGROUND

The elimination of malaria in Southeast Asia has become more challenging as a result of rising knowlesi malaria cases. In addition, naturally occurring human infections with other zoonotic simian malaria caused by Plasmodium cynomolgi and Plasmodium inui adds another level of complexity in malaria elimination in this region. Unfortunately, data on vectors which are responsible for transmitting this zoonotic disease is very limited.

METHODOLOGY/PRINCIPAL FINDINGS

We conducted longitudinal studies to investigate the entomological parameters of the simian malaria vectors and to examine the genetic diversity and evolutionary pattern of their simian Plasmodium. All the captured Anopheles mosquitoes were dissected to examine for the presence of oocysts, sporozoites and to determine the parous rate. Our study revealed that the Anopheles Leucosphyrus Group mosquitoes are highly potential competent vectors, as evidenced by their high rate of parity, survival and sporozoite infections in these mosquitoes. Thus, these mosquitoes represent a risk of human infection with zoonotic simian malaria in this region. Haplotype analysis on P. cynomolgi and P. inui, found in high prevalence in the Anopheles mosquitoes from this study, had shown close relationship between simian Plasmodium from the Anopheles mosquitoes with its vertebrate hosts. This directly signifies the ongoing transmission between the vector, macaques, and humans. Furthermore, population genetic analysis showed significant negative values which suggest that both Plasmodium species are undergoing population expansion.

CONCLUSIONS/SIGNIFICANCE

With constant microevolutionary processes, there are potential for both P. inui and P. cynomolgi to emerge and spread as a major public health problem, following the similar trend of P. knowlesi. Therefore, concerted vector studies in other parts of Southeast Asia are warranted to better comprehend the transmission dynamics of this zoonotic simian malaria which eventually would aid in the implementation of effective control measures in a rapidly changing environment.

Inter-Population Genetic Diversity and Clustering of Merozoite Surface Protein-1 (pkmsp-1) of Plasmodium knowlesi Isolates from Malaysia and Thailand

The genetic diversity of pkmsp-1 of Malaysian Plasmodium knowlesi isolates was studied recently. However, the study only included three relatively older strains from Peninsular Malaysia and focused mainly on the conserved blocks of this gene. In this study, the full-length pkmsp-1 sequence of recent P. knowlesi isolates from Peninsular Malaysia was characterized, along with Malaysian Borneo and Thailand pkmsp-1 sequences that were retrieved from GenBank. Genomic DNA of P. knowlesi was extracted from human blood specimens and the pkmsp-1 gene was PCR-amplified, cloned, and sequenced. The sequences were analysed for genetic diversity, departure from neutrality, and geographical clustering. The pkmsp-1 gene was found to be under purifying/negative selection and grouped into three clusters via a neighbour-joining tree and neighbour net inferences. Of the four polymorphic blocks in pkmsp-1, block IV, was most polymorphic, with the highest insertion-deletion (indel) sites. Two allelic families were identified in block IV, thereby highlighting the importance of this block as a promising genotyping marker for the multiplicity of infection study of P. knowlesi malaria. A single locus marker may provide an alternate, simpler method to type P. knowlesi in a population.

Predicting Plasmodium knowlesi transmission risk across Peninsular Malaysia using machine learning-based ecological niche modeling approaches

The emergence of potentially life-threatening zoonotic malaria caused by Plasmodium knowlesi nearly two decades ago has continued to challenge Malaysia healthcare. With a total of 376 P. knowlesi infections notified in 2008, the number increased to 2,609 cases in 2020 nationwide. Numerous studies have been conducted in Malaysian Borneo to determine the association between environmental factors and knowlesi malaria transmission. However, there is still a lack of understanding of the environmental influence on knowlesi malaria transmission in Peninsular Malaysia. Therefore, our study aimed to investigate the ecological distribution of human P. knowlesi malaria in relation to environmental factors in Peninsular Malaysia. A total of 2,873 records of human P. knowlesi infections in Peninsular Malaysia from 1st January 2011 to 31st December 2019 were collated from the Ministry of Health Malaysia and geolocated. Three machine learning-based models, maximum entropy (MaxEnt), extreme gradient boosting (XGBoost), and ensemble modeling approach, were applied to predict the spatial variation of P. knowlesi disease risk. Multiple environmental parameters including climate factors, landscape characteristics, and anthropogenic factors were included as predictors in both predictive models. Subsequently, an ensemble model was developed based on the output of both MaxEnt and XGBoost. Comparison between models indicated that the XGBoost has higher performance as compared to MaxEnt and ensemble model, with AUC_ROC values of 0.933 ± 0.002 and 0.854 ± 0.007 for train and test datasets, respectively. Key environmental covariates affecting human P. knowlesi occurrence were distance to the coastline, elevation, tree cover, annual precipitation, tree loss, and distance to the forest. Our models indicated that the disease risk areas were mainly distributed in low elevation (75-345 m above mean sea level) areas along the Titiwangsa mountain range and inland central-northern region of Peninsular Malaysia. The high-resolution risk map of human knowlesi malaria constructed in this study can be further utilized for multi-pronged interventions targeting community at-risk, macaque populations, and mosquito vectors.

A survey of simian Plasmodium infections in humans in West Kalimantan, Indonesia

The simian parasite Plasmodium knowlesi is the predominant species causing human malaria infection, including hospitalisations for severe disease and death, in Malaysian Borneo. By contrast, there have been only a few case reports of knowlesi malaria from Indonesian Borneo. This situation seems paradoxical since both regions share the same natural macaque hosts and Anopheles mosquito vectors, and therefore have a similar epidemiologically estimated risk of infection. To determine whether there is a true cross-border disparity in P. knowlesi prevalence, we conducted a community-based malaria screening study using PCR in Kapuas Hulu District, West Kalimantan. Blood samples were taken between April and September 2019 from 1000 people aged 6 months to 85 years attending health care facilities at 27 study sites within or close to jungle areas. There were 16 Plasmodium positive samples by PCR, five human malarias (two Plasmodium vivax, two Plasmodium ovale and one Plasmodium malariae) and 11 in which no species could be definitively identified. These data suggest that, if present, simian malarias including P. knowlesi are rare in the Kapuas Hulu District of West Kalimantan, Indonesian Borneo compared to geographically adjacent areas of Malaysian Borneo. The reason for this discrepancy, if confirmed in other epidemiologically similar regions of Indonesian Borneo, warrants further studies targeting possible cross-border differences in human activities in forested areas, together with more detailed surveys to complement the limited data relating to monkey hosts and Anopheles mosquito vectors in Indonesian Borneo.

Risk Association, Linkage Disequilibrium, and Haplotype Analyses of β-Like Globin Gene Polymorphisms with Malaria Risk in the Sabah Population of Malaysian Borneo

Single nucleotide polymorphisms (SNPs) in the β-like globin gene of the human hosts to the risk of malaria are unclear. Therefore, this study investigates these associations in the Sabah population, with a high incidence of malaria cases. In brief, DNA was extracted from 188 post-diagnostic blood samples infected with Plasmodium parasites and 170 healthy controls without a history of malaria. Genotyping of the β-like globin C-158T, G79A, C16G, and C-551T SNPs was performed using a polymerase chain reaction-restriction fragment length polymorphism approach. Risk association, linkage disequilibrium (LD), and haplotype analyses of these SNPs were assessed. This study found that the variant allele in the C-158T and C16G SNPs were protective against malaria infections by 0.5-fold, while the variant allele in the G79A SNP had a 6-fold increased risk of malaria infection. No SNP combination was in perfect LD, but several haplotypes (CGCC, CGCT, and CGGC) were identified to link with different correlation levels of malaria risk in the population. In conclusion, the C-158T, G79A, and C16G SNPs in the β-like globin gene are associated with the risk of malaria. The haplotypes (CGCC, CGCT, and CGGC) identified in this study could serve as biomarkers to estimate malaria risk in the population. This study provides essential data for the design of malaria control and management strategies.