Serological Evidence of Zika Virus Infection in Febrile Patients and Healthy Blood Donors in Sabah, Malaysian Borneo, 2017-2018.

Several Zika virus (ZIKV) seroprevalence studies have been conducted in Africa, Asia, Oceania, the Americas, and the Caribbean. However, studies on ZIKV seroprevalence are limited in Malaysia though several studies have shown that the disease is endemic in the Malaysian state of Sabah. To evaluate the seroprevalence of ZIKV infection, 818 serum samples were collected from febrile patients and healthy blood donors from the Kudat and Kota Kinabalu districts in Sabah from 2017 to 2018. They were screened for ZIKV infection by IgM and IgG ELISA, and positive ZIKV IgM samples were subjected to a 90% neutralization test for confirmation. Twenty-four (6% [95% CI 4 to 8]) confirmed and two (0.5% [95% CI 0.13 to 1.8]) probable ZIKV infections were detected among 400 febrile illness patients. Of 418 healthy blood donor samples, six (1.4% [95% CI 0.65 to 3]) were determined as confirmed ZIKV infections and six (1.4% [95% CI 0.65 to 3]) indicated probable ZIKV infection. This is the first study on the seroprevalence of ZIKV infections among patients and healthy blood donors in Sabah. Compared with previous studies in Malaysia, this study shows that the incidence of ZIKV infection has increased. It also suggests that a sero-surveillance system is essential to determine the circulation of ZIKV in Sabah, Malaysia.

Recent Incidence of Human Malaria Caused by Plasmodium knowlesi in the Villages in Kudat Peninsula, Sabah, Malaysia: Mapping of The Infection Risk Using Remote Sensing Data.

Plasmodium knowlesi (Pk) is a malaria parasite that naturally infects macaque monkeys in Southeast Asia. Pk malaria, the zoonosis transmitted from the infected monkeys to the humans by Anopheles mosquito vectors, is now a serious health problem in Malaysian Borneo. To create a strategic plan to control Pk malaria, it is important to estimate the occurrence of the disease correctly. The rise of Pk malaria has been explained as being due to ecological changes, especially deforestation. In this research, we analysed the time-series satellite images of MODIS (MODerate-resolution Imaging Spectroradiometer) of the Kudat Peninsula in Sabah and created the "Pk risk map" on which the Land-Use and Land-Cover (LULC) information was visualised. The case number of Pk malaria of a village appeared to have a correlation with the quantity of two specific LULC classes, the mosaic landscape of oil palm groves and the nearby land-use patches of dense forest, surrounding the village. Applying a Poisson multivariate regression with a generalised linear mixture model (GLMM), the occurrence of Pk malaria cases was estimated from the population and the quantified LULC distribution on the map. The obtained estimations explained the real case numbers well, when the contribution of another risk factor, possibly the occupation of the villagers, is considered. This implies that the occurrence of the Pk malaria cases of a village can be predictable from the population of the village and the LULC distribution shown around it on the map. The Pk risk map will help to assess the Pk malaria risk distributions quantitatively and to discover the hidden key factors behind the spread of this zoonosis.