METHODS: This is a review of the published literature related to the outbreak with the focus on human diseases.
RESULTS: The encephalitis was caused by a newly discovered paramyxovirus related to Hendra virus, later named Nipah virus. There were 265 patients with acute encephalitis. The disease is thought to spread from pig to man through close contact. The risk of human-to-human spread is thought to below. The disease affected mainly adult Chinese males, half of whom had affected family members. The disease presented mainly as acute encephalitis with a short incubation period of less than two weeks, with the main symptoms of fever, headache, and giddiness followed by coma. Distinctive clinical signs include segmental myoclonus, areflexia and hypotonia, hypertension, and tachycardia. Initial cerebrospinal fluid was abnormal in 75% of patients. Serology was helpful in confirming the diagnosis. Magnetic resonance imaging showed distinctive changes of multiple, discrete, and small high signal lesions, best seen with fluid-attenuated inversion recovery (FLAIR) sequences. Mortality was high at 40% and death was probably due to severe brainstem involvement. The main necropsy finding in acute encephalitis was that of disseminated microinfarction associated with vasculitis and direct neuronal involvement. Ribavirin was able to reduce the mortality by 36%. Relapse encephalitis was seen in 7.5% of those who recovered from acute encephalitis, and late-onset encephalitis in 3.4% of those with initial non-encephalitic or asymptomatic diseases. The mean interval between initial illness and the onset of the complication was 8.4 months. The relapse and late-onset encephalitis which manifested as focal encephalitis arose from recurrent infection.
CONCLUSION: Nipah virus, a recently discovered paramyxovirus, causes a unique encephalitis with high mortality as well as relapse and late-onset encephalitis. The infection is mainly spread from pigs to man.
METHODS: An agent-based model (ABM) is a relatively new approach that provides a framework for analyzing the heterogeneity of the interactions, along with biological and environmental factors in such complex systems. The objective of this research is to design and develop an ABM that uses Geospatial Information System (GIS) capabilities, biological behaviors of vectors and reservoir hosts, and an improved Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model to explore the spread of ZCL. Various scenarios were implemented to analyze the future ZCL spreads in different parts of Maraveh Tappeh County, in the northeast region of Golestan Province in northeastern Iran, with alternative socio-ecological conditions.
RESULTS: The results confirmed that the spread of the disease arises principally in the desert, low altitude areas, and riverside population centers. The outcomes also showed that the restricting movement of humans reduces the severity of the transmission. Moreover, the spread of ZCL has a particular temporal pattern, since the most prevalent cases occurred in the fall. The evaluation test also showed the similarity between the results and the reported spatiotemporal trends.
CONCLUSIONS: This study demonstrates the capability and efficiency of ABM to model and predict the spread of ZCL. The results of the presented approach can be considered as a guide for public health management and controlling the vector population .
METHODOLOGY/PRINCIPAL FINDINGS: A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam) as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines).
CONCLUSIONS/SIGNIFICANCE: We have produced the first map of P. knowlesi malaria risk, at a fine-scale resolution, to identify priority areas for surveillance based on regions with sparse data and high estimated risk. Our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. Considering malaria elimination goals, areas for prioritised surveillance are identified.