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Objective: The objective of this study was to investigate the frequency and drug resistance of Salmonella typhi in district Buner, Khyber Pakhtunkhwa. Material & Methods: This cross-section study was conducted at District Head Quarter Hospital Buner and private diagnostic centers from Jan 2020 to May 2021. A total of 460 blood samples were collected from OPD patients reported with signs and symptoms of Typhoid fever. Samples were cultured on blood and MacConkey agar, incubated at 37° for 24 hours. Bacterial identification was done on colony morphology, gram staining, and polyvalent antisera for strain identification. Finally, antibiotic susceptibility testing was done for the isolated bacteria. All commonly prescribed first-line and second option antibiotics were tested on Mueller Hinton agar by Kirby Bauer disk diffusion method following CLSI guidelines 2020. Result: A total of 240 out of 460 samples showed bacterial growth where Salmonella typhi was found in 98 (40.8%) cases. Among them, 28(28.6%) were reported as MDR while 1 (17.4%) were XDR. Out of the XDR, 4 strains were found resistant to Vancomycin and clarithromycin as well. The isolated S. typhi was 100% sensitive to Meropenem, and Azithromycin, however showed 100% resistance to Aztreonam, Ampicillin, and Cotrimoxazole. Prevalence of S. typhi was more (50%) in females while resistance was reported more in age group 20-40 years. Conclusion: The frequency of Salmonella typhi at district Buner was 41% in patients reported with high grade fever where 28% of the strains reported were multidrug resistant. Some extended spectrum drug-resistant S. typhi and Vancomycin and Clarithromycin resistant strains were also reported which is alarming. Meropenem, and Azithromycin were the only drugs effective against most of the strains. However, resistance to these drugs may develop soon if we do not stop empirical excessive use of antibiotics. [ABSTRACT FROM AUTHOR]

During the span of August–October, 2017 a major outbreak of Dengue fever happened in Khyber Pakhtunkhwa province of Pakistan. Cases were reported from all the major cities and rural areas, but Peshawar was more severely hit with more than half of the total cases belonging to central Peshawar city. The epidemic patterns reveal that dengue fever cases were mostly reported for plain areas and also low altitude mountainous regions. We employed the principle of maximum entropy to establish the underlying distribution of dengue presences and background data. A geostatistical analysis was conducted by modelling the spatial structure of the dengue fever risk and estimating the prediction maps with corresponding uncertainty taking into account some of the most significant covariates. The prediction maps were created using binomial kriging with a binary logistic drift. The analysis was carried out for the whole province as well as subregions to have a closer look of the spatial distribution at local level. Our results show that our methodology performed well. Vector distribution, population density, and distance to roads were found to significantly affecting the spatial distribution of risk and gives very informative pattern. [ABSTRACT FROM AUTHOR]