The spatial–temporal assessment of vector diseases is imperative to design effective action plans and establish preventive strategies. Therefore, such assessments have potential public health planning-related implications. In this context, we here propose an integrated spatial disease evaluation (I-SpaDE) framework. The I-SpaDE integrates various techniques such as the Kernel Density Estimation, the Optimized Hot Spot Analysis, space–time assessment and prediction, and the Geographically Weighted Regression (GWR). It makes it possible to systematically assess the disease concentrations, patterns/trends, clustering, prediction dynamics, and spatially varying relationships between disease and different associated factors. To demonstrate the applicability and effectiveness of the I-SpaDE, we apply it in the second largest city of Pakistan, namely Lahore, using Dengue Fever (DF) during 2007–2016 as an example vector disease. The most significant clustering is evident during the years 2007–2008, 2010–2011, 2013, and 2016. Mostly, the clusters are found within the city’s central functional area. The prediction analysis shows an inclination of DF distribution from less to more urbanized areas. The results from the GWR show that among various socio-ecological factors, the temperature is the most significantly associated with the DF followed by vegetation and built-up area. While the results are important to understand the DF situation in the study area and have useful implications for public health planning, the proposed framework is flexible, replicable, and robust to be utilized in other similar regions, particularly in developing countries in the tropics and sub-tropics.

Dengue fever (DF) is a national health problem in Pakistan. It has become endemic in Lahore after its recent reemergence in 2016. This study investigates the impacts of climatic factors (temperature and rainfall) on DF transmission in the district of Lahore through statistical approaches. Initially, the climatic variability was explored using a time series analysis on climatic factors from 1970 to 2012. Furthermore, ordinary and multiple linear regression analyses were used to measure the simulating effect of climatic factors on dengue incidence from 2007 to 2012. The time series analysis revealed significant annual and monthly variability in climatic factors, which shaped a dengue-supporting environment. It also showed a positive temporal relationship between climatic factors and DF. Moreover, the regression analyses revealed a substantial monthly relationship between climatic factors and dengue incidence. The ordinary linear regression of rainfall versus dengue showed monthly R² = 34.2%, whereas temperature versus dengue presented R² = 38.0%. The multiple regression analysis showed a monthly significance of R² = 44.6%. Consequently, our study shows a substantial synergism between dengue and climatic factors in Lahore. The present study could help in unveiling new ways for health prediction modeling of dengue and might be applicable in other subtropical and temperate climates.

Urban expansion is a serious threat, and many cities worldwide face unorganized expansion issues. This problem is widespread in developing countries, especially in Pakistan and Bahawalnagar, South Punjab's essential and historical city. The urban area has increased and created so many problems in cities, including food security, loss of agricultural land, the stress on educational and health facilities, the economy, housing accessibility and affordability, an increase in land prices and also an increase in the gap between rich and poor. This research analyses urban expansion through satellite data from 1990, 2000, 2010, and 2020. Supervised classification results show that the urban area increased from 1235 acres to 2717 acres from 1990 to 2020, and the agriculture area decreased from 4446 acres to 3458 acres from 1990 to 2020. Prediction simulation also shows that the agriculture area will decrease and the built-up area will increase. The impacts are analyzed through questionnaire data. Most respondents agree and strongly agree that the social and economic problems have increased in the last few decades due to the expansion. This study clarifies the scenario and provides the baseline for the sustainable management of the city for present and future needs.