The impact of demographic trends on economic growth ? productivity in Pakistan (1980-2007)

This paper seeks to examine the impact of demographic variables on economic growth in Pakistan. A long-run relationship between the variables has been found by applying Johanson?s Co-integration Technique after finding the series I(1). The Error Correction Model (ECM) has been applied to streamline the short-run and long- run impacts of the variables on economic growth. Population has a positive but decreasing impact on economic growth in the long run. Trade liberalisation and Human Capital Formation have a negative impact on globalisation in the long run and an insignificant impact in the short run. As a result of an increase in unemployment in the labour market in the short run, Life Expectancy, Labour Productivity Per Capita and Population Growth Rate have a negative impact on economic growth. This analysis will help decision makers in developing strategies and policies to accelerate economic growth, human capital formation and trade liberalisation in Pakistan

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Bivariate cointegration between poverty and environment: a case study of Pakistan (1980-2009)

The objective of this paper is to empirically investigate a two-way statistical relationship between the agriculture environment and rural poverty. To recognise the relationship between the two variables, a time series, co-integration and Granger causality tests have been employed. Secondary data pertaining to Pakistan from 1980-2009 on rural poverty and environmental factors (such as commercial energy consumption, water availability and total cropped area) have been used for the analysis. The empirical results only moderately support the conventional view that rural poverty has a significant long-term casual effect on environmental proxies in Pakistan. The present study finds evidence of uni-directional causality between poverty and the environment in the context of the agriculture sector in Pakistan.rural poverty, environmental degradation, cointegration, uni-directional, bi-directional, Granger causality test,

Strata-bound Dolomitization in the Eocene Laki Formation, Matyaro Jabal Area Lakhi Range, Sindh, Pakistan

The limestone of Eocene age Laki Formation of Matyaro Jabal area, Lakhi Range SindhPakistan has been studied to see different sedimentary features and diagenetic overprinting. The most diagnostic diagenetic feature of the Laki Formation is the formation of strata bound dolostone over extensive area. The dolostone beds which are separated by non-dolomitic limestone have developed at three different stratigraphic levels whose thickness vary from few centimeters to about 5 meters. Interbedded non dolomitic limestone is characterized by highly fossiliferous to less fossiliferous white chalky limestone with significant secondary porosity. The dolostone beds make lower erosional contact with chalky limestone while upper contact is sharp as well as transitional. The dolostone beds are very hard to soft with well developed dissolution cavities and karstification horizons. As a result of dolostone formation, the primary sedimentary features of rock fabrics and bioclasts are poorly preserved. However, few bioclastic grains show partial preservation with enhanced dissolution and biomoldic porosity. Dolomitization and different porosity types such as; intragranular, vuggy, molidic, intercrystalline, fracture and fenestral have made the limestone of Laki Formation as potential hydrocarbon reservoir rock. The mechanism of stratabound dolostone formation within Laki Formation is due to the mixing of seawater and fresh water with optimum Mg:Ca ratio. The Mg rich sea-water circulated through highly porous and permeable strata which was responsible for stratabound dolostone formation in the Laki Formation. The extrinsic factors such as sea level fluctuations and tectonics also played a vital role for dissolution along with porosity and permeability enhancement followed by dolomitization

Effects of decompression on pain, range of motion and function in patients with acute vs chronic lumbar radiculopathy

The purpose of this study was to determine the effects of manual lumbar decompression on pain, range of motion, and function in patients with acute vs chronic lumbar radiculopathy. Thirty patients fulfilling the eligibility criteria at Tehsil Headquarter Civil Hospital Daska were randomly placed into three groups: acute group (n=10), chronic group (n=10), and control group (n=10). Mean age of the participants was 33.3±8.5 years and the mean body mass index was 25.0±4.4. There were 12 males and 21 female participants. Group A and Group B were treated with decompression, lumbar mobilisation, hot packs, TENS and exercise therapy, while the patients in Group C were treated with lumbar mobilisation, hot packs and exercise therapy. ---continu

Associations of the COVID-19 pandemic with the reported incidence of important endemic infectious disease agents and syndromes in Pakistan

Abstract Background Persons in Pakistan have suffered from various infectious diseases over the years, each impacted by various factors including climate change, seasonality, geopolitics, and resource availability. The COVID-19 pandemic is another complicating factor, with changes in the reported incidence of endemic infectious diseases and related syndromes under surveillance. Methods We assessed the monthly incidence of eight important infectious diseases/syndromes: acute upper respiratory infection (AURI), viral hepatitis, malaria, pneumonia, diarrhea, typhoid fever, measles, and neonatal tetanus (NNT), before and after the onset of the COVID-19 pandemic. Administrative health data of monthly reported cases of these diseases/syndromes from all five provinces/regions of Pakistan for a 3-year interval (March 2018–February 2021) were analyzed using an interrupted time series approach. Reported monthly incidence for each infectious disease agent or syndrome and COVID-19 were subjected to time series visualization. Spearman’s rank correlation coefficient between each infectious disease/syndrome and COVID-19 was calculated and median case numbers of each disease before and after the onset of the COVID-19 pandemic were compared using a Wilcoxon signed-rank test. Subsequently, a generalized linear negative binomial regression model was developed to determine the association between reported cases of each disease and COVID-19. Results In late February 2020, concurrent with the start of COVID-19, in all provinces, there were decreases in the reported incidence of the following diseases: AURI, pneumonia, hepatitis, diarrhea, typhoid, and measles. In contrast, the incidence of COVID was negatively associated with the reported incidence of NNT only in Punjab and Sindh, but not in Khyber Pakhtunkhwa (KPK), Balochistan, or Azad Jammu & Kashmir (AJK) & Gilgit Baltistan (GB). Similarly, COVID-19 was associated with a lowered incidence of malaria in Punjab, Sindh, and AJK & GB, but not in KPK and Balochistan. Conclusions COVID-19 was associated with a decreased reported incidence of most infectious diseases/syndromes studied in most provinces of Pakistan. However, exceptions included NNT in KPK, Balochistan and AJK & GB, and malaria in KPK and Balochistan. This general trend was attributed to a combination of resource diversion, misdiagnosis, misclassification, misinformation, and seasonal patterns of each disease

Improvement of the predictive performance of landslide mapping models in mountainous terrains using cluster sampling

Landslide predictive performance is expected to vary with different sampling techniques, such as landslide random and cluster sampling. Current advancements in remote sensing technologies and machine learning (ML) have enhanced landslide prediction performance. The Himalayan Mountain range in Pakistan poses an unadorned threat to the ecosystem and valley population because of landslide occurrence. The present study explores, and tests alternative sampling technique based on spatial pattern characterization in the wake of increased landslide prediction efficacy, rather than a renowned random technique for training and testing sampling. Thereupon, landslide inventory data with 17 geo-environmental factors (i.e. topographic, hydrological and seismic factors) were determined. Landslide cluster patterns were confirmed by the Nearest Neighbor Index (NNI) method and after getting the cluster patterns, the predicted performance of landslide sampling was tested using ML and statistical methods. Advanced ML algorithms including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Naive Bayes (NB), K-nearest Neighbors (KNN) and statistical methods including Weight-of-Evidence (WofE) and Logistic Regression (LR) were used and validated. The landslide-prone district of Azad Jammu and Kashmir (Neelum Valley), Kashmir Himalayas, Pakistan, was selected as a case study. Prediction performance rates are high with area under the curve (AUC) ranging from 0.802 to 0.912; accuracy (ACC) ranges from 0.78 to 0.89, and kappa ranges from 0.50 to 0.68 with cluster sampling technique, whereas the performance was low with random sampling technique, with AUC ranges from 0.768 to 0.895; ACC ranges from 0.74 to 0.86 and kappa ranges from 0.48 to 0.64. The descending order of accuracy of the six algorithms was XGboost, RF, KNN, NB, LR and WofE. Our results confirmed that the landslides followed cluster patterns in the study area, and ML algorithms with cluster training samples positively affected landslide susceptibility prediction with a statistically significant difference. The outcomes support the hypothesis that using landslides spatial natural existence, as training samples, instead of random concepts, improves the prediction ability; and highlights that alternative landslide partitioning technique could be a practicable and robust choice for landslides prediction modelling