Geospatial techniques for environmental modeling of mosquito breeding habitats at Suez Canal Zone, Egypt

AbstractEgypt is currently witnessing a number of mega projects, along the axis of Suez Canal, which consequently have a great effect on environment and its biological components including mosquito vectors of diseases. This study is an attempt to explore the use and efficiency of integrated remote sensing-GIS techniques and field surveys for detection of mosquito breeding habitats at Suez Canal Zone. Remote sensing and field surveys provided the necessary verified ground truth information to the present study. A corrected Landsat8 image, acquired in Jan. 2015, was utilized to produce NDVI, NDMI and LST to identify environmental variables associated with mosquitoes breeding habitats. Concurrently, a GIS model was developed to predict probable mosquito habitats and areas under environmental risk of diseases transmission. Results revealed that Culex pipiens and Ochlerotatus detritus are the most abundant species in Suez Canal Zone recording total number of 362 larvae (51.86%) and 244 larvae (34.96%), respectively. The model predicted that Ismailia is the most subjected Suez Canal Governorate to mosquito borne diseases. It recorded the maximum levels of high risk, risk and vulnerable areas to mosquito proliferation; 6.06km2 (64.26%), 954.65km2 (54.58%) and 152.87km2 (80.09%), respectively. The developed prediction model achieved an accuracy of 80.95% and increased to 100% at sites where predicted larval habitats were ascertained by in-situ checks

Predicting the Current and Future Potential Distributions of Lymphatic Filariasis in Africa Using Maximum Entropy Ecological Niche Modelling

Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF), in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease) in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence

Extended Poisson Lomax Distribution

The main goal of this article is to introduce a new extension of the continuous Lomax distribution with a strong physical motivation. Some of its statistical properties such as moments, incomplete moments, moment generating function, quantile function, random number generation, quantile spread ordering and moment of the reversed residual life are derived. Two applications are provided to illustrate the importance and flexibility of the new model

Comparative phylogeography of Aedes mosquitoes and the role of past climatic change for evolution within Africa

Open Access Journal; Published online: 16 Feb 2018The study of demographic processes involved in species diversification and evolution ultimately provides explanations for the complex distribution of biodiversity on earth, indicates regions important for the maintenance and generation of biodiversity, and identifies biological units important for conservation or medical consequence. African and forest biota have both received relatively little attention with regard to understanding their diversification, although one possible mechanism is that this has been driven by historical climate change. To investigate this, we implemented a standard population genetics approach along with Approximate Bayesian Computation, using sequence data from two exon‐primed intron‐crossing (EPIC) nuclear loci and mitochondrial cytochrome oxidase subunit I, to investigate the evolutionary history of five medically important and inherently forest dependent mosquito species of the genus Aedes. By testing different demographic hypotheses, we show that Aedes bromeliae and Aedes lilii fit the same model of lineage diversification, admixture, expansion, and recent population structure previously inferred for Aedes aegypti. In addition, analyses of population structure show that Aedes africanus has undergone lineage diversification and expansion while Aedes hansfordi has been impacted by population expansion within Uganda. This congruence in evolutionary history is likely to relate to historical climate‐driven habitat change within Africa during the late Pleistocene and Holocene epoch. We find differences in the population structure of mosquitoes from Tanzania and Uganda compared to Benin and Uganda which could relate to differences in the historical connectivity of forests across the continent. Our findings emphasize the importance of recent climate change in the evolution of African forest biota