Malaria is one of the major public health issues globally. Malaria infection spreads through mosquito bites from infected female Anopheles mosquitoes. This study aims to conduct a systematic review and meta-analysis on malaria prevalence in Pakistan from 2006 to 2021. We searched PubMed, Science Direct, EMBASE, EMCare, and Google Scholar to acquire data on the prevalence of malaria infections. We performed a meta-analysis with a random-effects model to obtain the pooled prevalence of malaria, Plasmodium vivax, and Plasmodium falciparum. Meta-analysis was computed using R 4.1.2 Version statistical software. I² and time series analysis were performed to identify a possible source of heterogeneity across studies. A funnel plot and the Freeman-Tukey Double Arcsine Transformed Proportion were used to evaluate the presence of publication bias. Out of the 315 studies collected, only 45 full-text articles were screened and included in the final measurable meta-analysis. Pooled malaria prevalence in Pakistan was 23.3%, with Plasmodium vivax, Plasmodium falciparum, and mixed infection rates of 79.13%, 16.29%, and 3.98%, respectively. Similarly, the analysis revealed that the maximum malaria prevalence was 99.79% in Karachi and the minimum was 1.68% in the Larkana district. Amazingly, this systematic review and meta-analysis detected a wide variation in malaria prevalence in Pakistan. Pakistan's public health department and other competent authorities should pay close attention to the large decrease in mosquito populations to curb the infection rate.

Prostate cancer is a significant public health issue, ranking as the second most common cancer and the fifth leading cause of cancer-related deaths in men. In Pakistan, the prevalence of prostate cancer varies significantly across published articles. This study aimed to determine the pooled prevalence of prostate cancer and its associated risk factors in Pakistan. MEDLINE (via PubMed), Web of Science, Google Scholar, and local databases were searched from inception until March 2023, using key search terms related to the prevalence of prostate cancer. We considered a random-effects meta-analysis to derive the pooled prevalence and relative risks with 95% CIs. Two investigators independently screened articles and performed data extraction and risk of bias analysis. We also conducted meta-regression analysis and stratification to investigate heterogeneity. This study protocol was registered at PROSPERO, number CRD42022376061. Our meta-analysis incorporated 11 articles with a total sample size of 184,384. The overall pooled prevalence of prostate cancer was 5.20% (95% CI: 3.72–6.90%), with substantial heterogeneity among estimates (I² = 98.5%). The 95% prediction interval of prostate cancer was ranged from 1.74%–10.35%. Subgroup meta-analysis revealed that the highest pooled prevalence of prostate cancer was in Khyber Pakhtunkhwa (8.29%; 95% CI: 6.13–10.74%, n = 1), followed by Punjab (8.09%; 95% CI:7.36–8.86%, n = 3), while the lowest was found in Sindh (3.30%; 95% CI: 2.37–4.38%, n = 5). From 2000 to 2010 to 2011–2023, the prevalence of prostate cancer increased significantly from 3.88% (95% CI: 2.72–5.23%) to 5.80% (95% CI: 3.76–8.24%). Our meta-analysis provides essential insights into the prevalence of prostate cancer in Pakistan, highlighting the need for continued research and interventions to address this pressing health issue.

In cricket, the ranking of players or teams has a significant impact on determining the top player or team. The goal of this study is to forecast Test Cricket Match Outcomes and then create a team rating based on these predictions. In general, in any sport, the team with the most rating points is regarded as the greatest, and the teams are ranked based on their ratings. The Bradley-Terry model is used to forecast match outcomes using data from January 3rd, 2010 through August 25th, 2020, for a total of 444 matches. The teams of the top ten cricket-playing nations have been ranked using model rating. The rating of the underlying model is also compared to the updated 25th August 2020 official ICC ranking, which yields roughly similar findings. To improve model accuracy, the home ground effect is added, which has a substantial impact on team performance. After the home factor is added as a potential covariate, the model ranking is compared to the ICC ranking, which yields more closed results. Later, when these two results are compared with or without the home ground component, there is a significant improvement between them. To assess team performance, winning probabilities and confidence intervals are produced for each participating nation using model estimate coefficients. Three performance indicators are computed for the top ten playing teams, taking away and home ground factors into account. When these real data were compared, the home ground factor produced more precise results than removing the specified covariate. The outcomes of the suggested approach are also compared to predetermined odds that differ marginally.

Psychiatric outpatients receiving long-term psychotropic therapy are at increased risk of oral health problems because of medication-related xerostomia, im

This study discusses the challenges associated with estimating the population coefficient of variation using sampling survey techniques. Yunusa et al. (2021) motivate this study. We further improve these estimators to estimate this study's unknown population coefficient of variation. Using two populations as examples, empirical results indicate that the proposed estimator provides more accurate estimates of population variability since it is more efficient. Further research and validation are recommended to establish the robustness and generalizability of the proposed estimator.

This study utilized a cross-sectional survey design and focused on female patients who were hospitalized to Lady Reading Hospital in Peshawar. A total of 132 patients were included in this survey. Data collection was conducted using the convenience sampling technique. The female patients included in this study were postnatal women who were singletons and above the age of 18, and had no problems linked to pregnancy. Data analysis was conducted using version 22 of SPSS. The Chi-square test was utilized for association. The Objective was to assess the influence of physical activity (PA) throughout pregnancy on the occurrence of maternal obesity and pre-term delivery A total of 132 people, all above the age of 18, took part in this study. The average age of the group was 25 years with a standard deviation of 5.37. The occurrence rates of normal vaginal delivery, caesarean section, and pre-term delivery were 66.5%, 33.3%, and 15.2% respectively. Nevertheless, the occurrence of low, moderate, and strong levels of physical activity were 32 (24.2%), 100 (75.8%), and 0 (0%) respectively. A significant correlation was seen between prenatal physical activity and method of delivery (P-value = 0.00), but no significant correlation was identified between prenatal physical activity and pre-term delivery (P-value = 0.631). Furthermore, a significant correlation was seen between age and manner of delivery (P-value = 0.006), but no significant correlation was discovered between age and pre-term delivery (P-value = 0.157). The findings of this study indicate that engaging in physical activity during pregnancy has a beneficial effect on the method of delivery, but it does not have any influence on the occurrence of pre-term birth. This study also determined that there is a correlation between age and MOD (mode of delivery), and no correlation was discovered with pre-term delivery.