Monitoring larval populations of 'Aedes aegypti' in different residential districts of Jeddah governorate, Saudi Arabia
House-to-house surveys of larval population of 'Aedes aegypti' were conducted to determine the importance of house index for each habitat in Jeddah governorate. In this study, we aimed to survey and monitor mosquito population and potential breeding sites by using House index (HI), Container index (CI), and Breteau index (BI). The statistical analysis showed that the presence of larval stages of 'Ae. aegypti' reported throughout the year inside houses in the studied locations (Ghuleel, Al-Balad, Al-Jameiah, Al-Nazlah Al-Yamaneyyah, and Al-Safa) with some significant differences among investigated areas showed that Ghuleel had highest and Al-Safa lowest in density of larvae, respectively. House indices of each study area compared with the highest ratio of standard WHO (5-10%) were as follows: 8.7, 7.6, 6.6, 6.22 and 4%, respectively, for the above sites (P<0.05). The results showed that there were significant differences among types of containers of water in the inspected houses. Large containers were most significant compared with medium and small containers. Container index (CI) was 12% (Ghuleel), 13% (Al-Balad) and 14% (Al-Jameiah), 12% (Al-Nazlah Al- Yamaneyyah) and 9% (Al-Safa), whereas Breteau index (BI) was 8, 6.6, 4.7, 4.5 and 1.43%, respectively. Significant increase in the density of larvae was found in November, March, June and January due to the effect of the environmental factors including temperature and humidity.
Modeling Interactions Between Vector-Borne Diseases and Environment Using GIS
This book of modelling interactions between vector-borne diseases and the environment using geographic information system (GIS) methods fills many literature gaps. The book shows how GIS-based approaches provide innovative geographical methods with the capability of mapping and modelling such interactions with high accuracy. It shows how GISs can be used to merge satellite images with ground observations of vector demographics and disease incidence more accurately. It comes with the hope of increasing the ability of controlling the global prevalence of vector-borne diseases, such as dengue fever, malaria, and Rift Valley fever, which have increased dramatically in recent times, causing medical, environmental, and economic issues for most of the tropical and subtropical countries. Modelling interaction between vector-borne diseases and the environment using GISs increases understanding of the distribution of vector-borne disease incidence and vectors such as mosquitoes in time and space, which can be a major foundation for control and management programs for vector-borne diseases. The geographical methods used in this book show how knowledge of when and where disease cases and vectors occur enables the formulation of disease causation hypotheses for vectors and cases with unknown or poorly characterized aetiology, identification of areas at risk for disease, and design of efficient surveillance and control programs. These methods for modelling risks of diseases and vectors can also be implemented at local, country, and regional levels by vector-borne disease program managers, health officers and workers, and policy makers to ensure their optimal contribution to prevention, control, acceptance, and sustainability of programs. In addition, the book shows a variety of GIS implications in the planning of health interventions that can be used to enhance disease surveillance systems. It is useful for undergraduate and postgraduate students and postdoctoral researchers involved in epidemiological studies, particularly of vector-borne diseases, especially when they require the use of geographical modelling techniques in a GIS environment. The geographical modelling and analytical techniques described in this book are also valuable for researchers, workers, and students dealing with geographical data in the areas of entomology, environmental health, ecology, environmental science, public health, crime, geography, parasitological, and statistics. There is no doubt that GIS-based approaches will play a more significant role in such applications.