Short Communication:  Leptospirosis control based on eco-social factors:  Modeling combination in Demak, Central Java, Indonesia

Djati, Rr. Anggun Paramita; Kusnoputranto, Haryoto; Utomo, Suyud Warno; Sakundarno, Mateus; Dewabrata, Pandji Wibawa; Fuad, Habiburrachman A. H.; Wicaksono, Mochammad Arief

doi:10.13057/biodiv/d211245

Cited by 2 publications

(1 citation statement)

References 19 publications

(23 reference statements)

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“…Our study also reported that the farmers connected more rats with the reduction of predators such as owls. Owl breeding can be an effective way of controlling rodents, as has been shown in other parts of Indonesia [30].…”

Section: Discussionmentioning

confidence: 80%

Leptospirosis in Ruminants in Yogyakarta, Indonesia: A Serological Survey with Mixed Methods to Identify Risk Factors

et al. 2021

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Leptospirosis is a zoonotic disease occurring worldwide with reproductive symptoms and production losses in livestock, while humans can suffer fatal renal failure. In Yogyakarta Special Province, Indonesia, there have been several outbreaks with high case fatality, demonstrating the public health importance, but there is limited understanding of the epidemiology. This study used an EcoHealth approach to ensure transdisciplinarity and community participation. Seroprevalence of Leptospira in animals was studied between October 2011 and May 2013 in 15 villages. Serum samples from 1404 cattle and 60 small ruminants were screened by a Microscopic Agglutination Test (MAT), first in pools, and then the individual positive samples were identified. Focus group discussions including farmers, village officials, and official stakeholders were used to explore knowledge and behavior of zoonotic diseases, particularly leptospirosis. Two small ruminants were seropositive for Leptospira icterohemorrhagiae. From the cattle, 3.7% were seropositive, and the most common serovars were Leptospira hardjo, followed by L. icterohemorrhagiae. Out of all farms, 5.6% had at least one positive cattle. Risk factor analyses showed that the risk of the farm being seropositive increased if the farmer used water from an open source, or if farming was not the main occupation. This study showed the presence of Leptospira spp. in ruminants in Yogyakarta and identified use of open water as a risk factor for the livestock. We also observed that the knowledge related to leptospirosis was low, and risky farm management practices were commonly employed.

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Section: Discussionmentioning

confidence: 80%

Leptospirosis in Ruminants in Yogyakarta, Indonesia: A Serological Survey with Mixed Methods to Identify Risk Factors

et al. 2021

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Spatio-temporal modeling of human leptospirosis prevalence using the maximum entropy model

Shirzad,

Alesheikh,

Asgharzadeh

et al. 2023

BMC Public Health

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Background Leptospirosis, a zoonotic disease, stands as one of the prevailing health issues in some tropical areas of Iran. Over a decade, its incidence rate has been estimated at approximately 2.33 cases per 10,000 individuals. Our research focused on analyzing the spatiotemporal clustering of Leptospirosis and developing a disease prevalence model as an essential focal point for public health policymakers, urging targeted interventions and strategies. Methods The SaTScan and Maximum Entropy (MaxEnt) modeling methods were used to find the spatiotemporal clusters of the Leptospirosis and model the disease prevalence in Iran. We incorporated nine environmental covariates by employing a spatial resolution of 1 km x 1 km, the finest resolution ever implemented for modeling Human Leptospirosis in Iran. These covariates encompassed the Digital Elevation Model (DEM), slope, displacement areas, water bodies, and land cover, monthly recorded Normalized Difference Vegetation Index (NDVI), monthly recorded precipitation, monthly recorded mean and maximum temperature, contributing significantly to our disease modeling approach. The analysis using MaxEnt yielded the Area Under the Receiver Operating Characteristic Curve (AUC) metrics for the training and test data, to evaluate the accuracy of the implemented model. Results The findings reveal a highly significant primary cluster (p-value < 0.05) located in the western regions of the Gilan province, spanning from July 2013 to July 2015 (p-value < 0.05). Moreover, there were four more clusters (p-value < 0.05) identified near Someh Sara, Neka, Gorgan and Rudbar. Furthermore, the risk mapping effectively illustrates the potential expansion of the disease into the western and northwestern regions. The AUC metrics of 0.956 and 0.952 for the training and test data, respectively, underscoring the robust accuracy of the implemented model. Interestingly, among the variables considered, the influence of slope and distance from water bodies appears to be minimal. However, altitude and precipitation stand out as the primary determinants that significantly contribute to the prevalence of the disease. Conclusions The risk map generated through this study carries significant potential to enhance public awareness and inform the formulation of impactful policies to combat Leptospirosis. These maps also play a crucial role in tracking disease incidents and strategically directing interventions toward the regions most susceptible.

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Short Communication: Leptospirosis control based on eco-social factors: Modeling combination in Demak, Central Java, Indonesia

Cited by 2 publications

References 19 publications

Leptospirosis in Ruminants in Yogyakarta, Indonesia: A Serological Survey with Mixed Methods to Identify Risk Factors

Leptospirosis in Ruminants in Yogyakarta, Indonesia: A Serological Survey with Mixed Methods to Identify Risk Factors

Spatio-temporal modeling of human leptospirosis prevalence using the maximum entropy model

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