Integrating Spatial Modelling and Space-Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan.

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.

A comprehensive assessment of environmental pollution by means of heavy metal analysis for oysters' reefs at Hab River Delta, Balochistan, Pakistan.

The heavy metal pollution status of oyster reefs has been assessed with respect to ten metals pollutants in seawater, sediments, and tissues of above two oysters (soft tissues and shells) for assessing the pollution status in a short food chain in Hab River Delta. The results showed that heavy metals accumulated in M. bilineata were higher than those in M. cuttackensis. Simultaneously, the population of M. bilineata species has been ironically decreasing as a results of high pollution. The determined concentrations revealed a significant differences in their profiles among sediments, seawater and bioaccumulation in tissues and shells of two native oysters. The present study also compared these metal concentrations with national and international database by applying different pollution indices. Heavy metals in all samples were above the national environmental quality standards (NEQS-Pakistan). High level of pollution with an alarming condition of Hab River Delta need more attention for coastal management.