Introduction Resistant strains of bacteria are rapidly emerging with increasing inappropriate use of antibiotics rendering them less efficacious. Self-purchasing of antibiotics particularly for viral infections is a key driver of inappropriate use, especially in lower- and middle-income countries. There is a particular issue in countries such as Pakistan. Consequently, there is a need to assess current rates of self-purchasing especially for reserve antibiotics to guide future policies. Aims Assess the extent of current antibiotic sales without a prescription in urban areas of Pakistan. Methodology A multicenter cross-sectional study was conducted in different areas of Punjab, Pakistan using Simulated Client technique. The investigators demanded different predefined antibiotics from WHO AWaRe groups without prescription. Three levels of demand were used to convince the pharmacy staff in order to dispense the antibiotic without a prescription. A data collection form was completed by simulated clients within 15 min of each visit. Results Overall 353 pharmacies and medical stores were visited out of which 96.9% pharmacies and medical stores dispensed antibiotics without demanding a prescription (82.7% at demand level 1 and 14.2% at demand level 2), with only 3.1% of pharmacies refusing to dispense antibiotics. The most frequently dispensed antibiotic was ciprofloxacin (22.1%). Surprisingly, even the reserve group antibiotics were also dispensed without a prescription. In only 25.2% visits, pharmacy staff guided patients about the use of antibiotics, and in only 11.0% pharmacists enquired about other medication history. Conclusion Currently, antibiotics are easily acquired without a legitimate prescription in Pakistan. There is a need for strict adherence to regulations combined with a multi-dimensional approach to enhance appropriate dispensing of antibiotics and limit any dispensing of WHO restricted antibiotics without a prescription.
The COVID-19 pandemic has significantly influenced antimicrobial use in hospitals, raising concerns regarding increased antimicrobial resistance (AMR) through their overuse. The objective of this study was to assess patterns of antimicrobial prescribing during the current COVID-19 pandemic among hospitals in Pakistan, including the prevalence of COVID-19. A point prevalence survey (PPS) was performed among 11 different hospitals from November 2020 to January 2021. The study included all hospitalized patients receiving an antibiotic on the day of the PPS. The Global-PPS web-based application was used for data entry and analysis. Out of 1024 hospitalized patients, 662 (64.64%) received antimicrobials. The top three most common indications for antimicrobial use were pneumonia (13.3%), central nervous system infections (10.4%) and gastrointestinal indications (10.4%). Ceftriaxone (26.6%), metronidazole (9.7%) and vancomycin (7.9%) were the top three most commonly prescribed antimicrobials among surveyed patients, with the majority of antibiotics administered empirically (97.9%). Most antimicrobials for surgical prophylaxis were given for more than one day, which is a concern. Overall, a high percentage of antimicrobial use, including broad-spectrums, was seen among the different hospitals in Pakistan during the current COVID-19 pandemic. Multifaceted interventions are needed to enhance rational antimicrobial prescribing including limiting their prescribing post-operatively for surgical prophylaxis.
This study compares the performance of four satellite-based rainfall products (SRPs) (PERSIANN-CCS, PERSIANN-CDR, SM2RAIN-ASCAT, and CHIRPS-2.0) in a semi-arid subtropical region. As a case study, Punjab Province of Pakistan was considered for this assessment. Using observations from in-situ meteorological stations, the uncertainty in daily, monthly, seasonal, and annual rainfall estimates of SRPs at pixel and regional scales during 2010–2018 were examined. Several evaluation indices (Correlation Coefficient (CC), Root Mean Square Error (RMSE), Bias, and relative Bias (rBias), as well as categorical indices (Probability of Detection (POD), Critical Success Index (CSI), and False Alarm Ration (FAR)) were used to assess the performance of the SRPs. The following findings were found: (1) CHIRPS-2.0 and SM2RAIN-ASCAT products were capable of tracking the spatiotemporal variability of observed rainfall, (2) all SRPs had higher overall performances in the northwestern parts of the province than the other parts, (3) all SRP estimates were in better agreement with ground-based monthly observations than daily records, and (4) on the seasonal scale, CHIRPS-2.0 and SM2RAIN-ASCAT were better than PERSIANN-CCS and PERSIANN. In all seasons, CHIRPS-2.0 and SM2RAIN-ASCAT outperformed PERSIANN-CCS and PERSIANN-CDR. Based on our findings, we recommend that hydrometeorological investigations in Pakistan’s Punjab Province employ monthly estimates of CHIRPS-2.0 and SM2RAIN-ASCAT products.
Performance assessment of satellite-based precipitation products (SPPs) is critical for their application and development. This study assessed the accuracies of four satellite-based precipitation products (PERSIANN-CDR, PERSIANN-CCS, PERSIANN-DIR, and PERSIANN) using data of in situ weather stations installed over the Himalayan Mountains of Pakistan. All SPPs were evaluated on annual, seasonal, monthly, and daily bases from 2010 to 2017, over the whole spatial domain and at point-to-pixel scale. The assessment was conducted using widely used evaluation indices (root mean square error (RMSE), correlation coefficient (CC), bias, and relative bias (rBias)) along with categorical indices (false alarm ratio (FAR), probability of detection (POD), success ratio (SR), and critical success index (CSI)). Results showed: (1) PERSIANN and PERSIANN-DIR products efficiently traced the spatio-temporal distribution of precipitation over the Himalayan Mountains. (2) On monthly scale, the estimates of all SPPs were more consistent with the reference data than on the daily scale. (3) On seasonal scale, PERSIANN and PERSIANN-DIR showed better performances than the PERSIANN-CDR and PERSIANN-CCS products. (4) All SPPs were less accurate in sensing daily light to medium intensity precipitation events. Subsequently, for future hydro-meteorological investigations in the Himalayan range, we advocate the use of monthly PERSIANN and PERSIANN-DIR products.
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