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  1. Cuenca PR, Key S, Jumail A, Surendra H, Ferguson HM, Drakeley CJ, et al.
    Adv Parasitol, 2021;113:225-286.
    PMID: 34620384 DOI: 10.1016/bs.apar.2021.08.006
    Within the past two decades, incidence of human cases of the zoonotic malaria Plasmodium knowlesi has increased markedly. P. knowlesi is now the most common cause of human malaria in Malaysia and threatens to undermine malaria control programmes across Southeast Asia. The emergence of zoonotic malaria corresponds to a period of rapid deforestation within this region. These environmental changes impact the distribution and behaviour of the simian hosts, mosquito vector species and human populations, creating new opportunities for P. knowlesi transmission. Here, we review how landscape changes can drive zoonotic disease emergence, examine the extent and causes of these changes across Southeast and identify how these mechanisms may be impacting P. knowlesi dynamics. We review the current spatial epidemiology of reported P. knowlesi infections in people and assess how these demographic and environmental changes may lead to changes in transmission patterns. Finally, we identify opportunities to improve P. knowlesi surveillance and develop targeted ecological interventions within these landscapes.
  2. Fornace KM, Surendra H, Abidin TR, Reyes R, Macalinao MLM, Stresman G, et al.
    Int J Health Geogr, 2018 06 18;17(1):21.
    PMID: 29914506 DOI: 10.1186/s12942-018-0141-0
    BACKGROUND: Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information.

    RESULTS: Using Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42-368) in Rizal and 493 m (IQR 258-886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.

    CONCLUSIONS: Results demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.

  3. Braima KA, Piera KA, Lubis IN, Noviyanti R, Rajahram GS, Kariodimedjo P, et al.
    medRxiv, 2024 Apr 06.
    PMID: 38633782 DOI: 10.1101/2024.04.04.24305339
    BACKGROUND: Zoonotic P. knowlesi and P. cynomolgi symptomatic and asymptomatic infections occur across endemic areas of Southeast Asia. Most infections are low-parasitemia, with an unknown proportion below routine microscopy detection thresholds. Molecular surveillance tools optimizing the limit of detection (LOD) would allow more accurate estimates of zoonotic malaria prevalence.

    METHODS: An established ultra-sensitive Plasmodium genus quantitative-PCR (qPCR) assay targeting the 18S rRNA gene underwent LOD evaluation with and without reverse transcription (RT) for P. knowlesi, P. cynomolgi and P. vivax using total nucleic acid preserved (DNA/RNA Shield™) isolates and archived dried blood spots (DBS). LODs for selected P. knowlesi-specific assays, and reference P. vivax- and P. cynomolgi-specific assays were determined with RT. Assay specificities were assessed using clinical malaria samples and malaria-negative controls.

    RESULTS: The use of reverse transcription improved Plasmodium species detection by up to 10,000-fold (Plasmodium genus), 2759-fold (P. knowlesi), 1000-fold (P. vivax) and 10-fold (P. cynomolgi). The median LOD with RT for the Kamau et al. Plasmodium genus RT-qPCR assay was ≤0.0002 parasites/μL for P. knowlesi and 0.002 parasites/μL for both P. cynomolgi and P. vivax. The LODs with RT for P. knowlesi-specific PCRs were: Imwong et al. 18S rRNA (0.0007 parasites/μL); Divis et al. real-time 18S rRNA (0.0002 parasites/μL); Lubis et al. hemi-nested SICAvar (1.1 parasites/μL) and Lee et al. nested 18S rRNA (11 parasites/μL). The LOD for P. vivax- and P. cynomolgi-specific assays with RT were 0.02 and 0.20 parasites/μL respectively. For DBS P. knowlesi samples the median LOD for the Plasmodium genus qPCR with RT was 0.08, and without RT was 19.89 parasites/uL (249-fold change); no LOD improvement was demonstrated in DBS archived beyond 6 years. The Plasmodium genus and P. knowlesi-assays were 100% specific for Plasmodium species and P. knowlesi detection, respectively, from 190 clinical infections and 48 healthy controls. Reference P. vivax-specific primers demonstrated known cross-reactivity with P. cynomolgi.

    CONCLUSION: Our findings support the use of an 18S rRNA Plasmodium genus qPCR and species-specific nested PCR protocol with RT for highly-sensitive surveillance of zoonotic and human Plasmodium species infections.

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