Foot and mouth disease (FMD) is one of the most contagious diseases of livestock with a significant economic impact affecting most countries in the world over the years. In Turkey, FMD is endemic, but there have not been national studies conducted to analyze spatiotemporal pattern of FMD yet. This study was carried out to identify the spatial and temporal distribution of FMD outbreaks in Turkey from January 2010 to December 2019, to guide the eradication following development of control programs against the disease. Thematic maps were produced to determine FMD sensitive regions and Box-Jenkins time series approach was used to analyze the temporal pattern of FMD. Between these dates, 6698 outbreaks and 246341 cases were reported in Turkey, FMD was recorded multiple times in 96.3% of the provinces (n = 78), and the average incidence of FMD outbreaks at the provincial level was calculated as 8.27/province year. As result of the spatial pattern of FMD, East and Central Anatolia were determined as the regions where the disease was observed intensely. The time series plot of the data showed a general not very regular trend although there was a downward trend with irregular variations. Although, there was no seasonal effect detected by the decomposition of time series, seasonal peaks in the outbreaks were observed, in the spring (n = 2087, 31.16%). In conclusion, the evaluation of spatial and temporal pattern based on FMD outbreaks that are common in Turkey will contribute to eradication of the disease.

Background and Objectives: Bleeding is a major cause of mortality in cases of acute myeloid leukemia (AML)-associated disseminated intravascular coagulation (DIC). The predictive power of the standard International Society on Thrombosis and Hemostasis (ISTH) score for bleeding in patients diagnosed with AML is limited. This study aimed to evaluate the performance of the standard ISTH score and modified versions in predicting bleeding among acute promyelocytic leukemia (APL, M3) and non-APL AML subgroups. Methods: This single-center, retrospective study included 190 AML patients (61 APL, 129 non-APL). The predictive power of the original ISTH score and eight different modified scores—incorporating parameters such as lactate dehydrogenase (LDH) and genetic positivity—for DIC-related bleeding was assessed using receiver operating characteristic (ROC) analysis. Results: In the APL group, the original ISTH score was statistically significant in predicting DIC-related bleeding (AUC = 0.727), but the modifications did not improve performance. In the non-APL AML group, the original score did not predict bleeding (AUC = 0.632, p = 0.079). However, a modified ISTH score excluding D-dimer and including LDH (≥800 mg/dL) and genetic positivity significantly improved prediction (AUC = 0.710, p = 0.005). This modification increased specificity from 48.2% to 60.7% and sensitivity from 76.5% to 82.4%. Conclusions: A subtype-specific approach is required to predict bleeding risk in AML-associated DIC. Modified ISTH scores remain suboptimal for APL; however, a modified score incorporating LDH and genetic status represents a promising tool to identify non-APL AML patients at risk of bleeding and warrants prospective validation.

Lumpy skin disease (LSD) is a serious, transboundary disease that affects cattle all over the world and results in considerable productivity losses. Although Türkiye’s first outbreak of LSD was reported in August 2013, there is very little information available about the outbreak’s spatiotemporal distribution or severity. GIS-based data analysis provides crucial tools for describing the spatial epidemiology of the disease by assessing the spatial distribution of LSD across time. This study used information on outbreaks reported to the the World Animal Health Organization (WOAH-OIE) between 2013 and 2021 to conduct a retrospective study on the epidemiology of LSD in Türkiye. Differences in the number of reported outbreaks and cases across different regions, provinces, months, and years were evaluated and descriptive statistics were calculated. In addition, spatial statistical tests (Local Moran’s I and Getis-Ord Gi*) and Geographical Information Systems (GIS) were used to assess LSD outbreaks that had taken place at the province level in Türkiye. Possible epidemiological clusters of LSD were identified. A total of 1787 outbreaks and 10109 cases of LSD were reported from 75 out of 81 provinces of Türkiye during the course of the nine-year period. Hotspots for the circulation of LSD were identified in the Aegean, Southeastern and Eastern regions using spatial cluster analyses and it was observed that the spatial autocorrelation of LSD cases is positive across the country. The findings from this study, it may help us comprehend the disease’s spatial character and offer authorities the beneficial information for surveillance efforts.

Peste des petits ruminants (PPR) is a viral disease affecting small ruminants and causes significant agricultural damage. The World Organization for Animal Health (OIE) has classified PPR as an animal disease that must be reported immediately. In this study was aimed to understand of spatial and seasonal epidemiology of PPR in Turkey and provide information by using Geographical Information Systems (GIS). Descriptive and analytical statistics were used in the study, logistic regression analysis was applied to assess the effect of season and species factors on PPR outbreaks occurring in Turkey. Data were obtained from the World Animal Health Information System (WAHIS) database of OIE. Between 2017-2019, 337 outbreaks, 18.467 cases and 11.526 deaths were reported 57 provinces of Turkey and the highest number of PPR outbreaks, cases and deaths were reported in The Central Anatolia Region. On time-wise examination, the PPR risk-areas revealed changes with different levels of endemicity. The Central Anatolia Region were the top outbreaks reported region during 2017-2018, whereas The Marmara Region reported more outbreaks during 2019. PPR outbreaks occurred throughout the year in all seasons, but were most frequently encountered during the winter season (December to February) and the results showed that seasonal and species factors are important in the spread of the disease. PPR has widely distributed throughout the country, and the epidemiological picture suggests that the disease has become an endemic infection in the country. The spatial and seasonal distribution of PPR in Turkey gives useful information on hotspot areas, allowing managers to make informed decisions about prevention and control in different parts of the country. In accordance with the PPR Global Control and Eradication Strategy, the study also outlines when and where extensive surveillance, vaccination, and biosecurity measures are required for the control and eradication of the disease in Turkey.

This study was aimed to understand the spatial and seasonal epidemiology of Newcastle disease (ND) in Türkiye using the outbreak data between 2017-2019 and also to calculate the case-fatality rates of this disease. It was also aimed to produce the maps by using Geographical Information Systems (GIS). Data were obtained from the World Animal Health Information System (WAHIS) database of the World Organization for Animal Health (OIE). Total number of 220 outbreaks of ND were registered in 47 provinces of Türkiye between this years. Accordingly, 88,372 poultry birds transmitted the disease. The highest number of ND outbreaks, cases and deaths was reported in The Black Sea Region. According to the regions there was a statistically significant difference in the number of outbreaks (P0.05). On the other hand the highest number of ND outbreaks, cases and deaths was reported in the spring season. As a result of the comparisons according to the seasons, there was a statistically significant difference in the number of deaths (P0.05). The spatial and seasonal distributions identified in this study should be taken into account while attempting to control the disease. Also, it is thought that the creation of spatial maps based on ND outbreaks that are common in Türkiye will contribute to the determination of the areas where precautions should be taken against the disease.

The aim of this study is to analyze the spatial pattern of sericulture in Türkiye with spatial analysis approaches, taking into account the data of 81 provinces, by creating a database based on Geographic Information Systems (GIS). This study employed data from the TURKSTAT, which included the amount of fresh cocoon produced and the silkworm egg boxes opened, between 2004-2022. In order to evaluate the relationship between the cocoon yield in each province and the cocoon yield in neighboring provinces, Moran's I measurements were made for the relevant time periods, and each period's Moran's I scatter plot was created. The Local Spatial Association Indicator (LISA) was used to assess the spatial structure of fresh cocoon yield. There was determined spatial clustering and a positive spatial association for cocoon yield, and all of the Moran's I values were found to be more than 0. The LISA maps were demonstrated the distinct local clustering patterns in the cocoon yield. More local clusters were identified (High-High or Low-Low) compared to local spatial outliers (High-Low or Low-High). High-High clusters were generally identified in the Marmara Region. Important implications have been obtained in terms of sustainability, such as how to take advantage of hotspot spillover effects and prioritize hotspot locations when allocating resources. As a result, spatial relations should be taken into account in the policies to be developed for sericulture and more activities should be carried out on sericulture.