Population Fluctuations and Abundance Indices of Mosquitoes (Diptera: Culicid), as the Potential Bridge Vectors of Pathogens to Humans and Animals in Mazandaran Province, Northern Iran.

BACKGROUND: Seasonal activity patterns of mosquitoes are essential as baseline knowledge to understand the transmission dynamics of vector-borne diseases. This study was conducted to evaluate the monthly dynamics of the mosquito populations and their relation to meteorological factors in Mazandaran Province, north of Iran. METHODS: Mosquito adults and larvae were collected from 16 counties of Mazandaran Province using different sampling techniques, once a month from May to December 2014. "Index of Species Abundance" (ISA) along with "Standardized ISA" (SISA) was used for assessing the most abundant species of mosquitoes based on the explanations of Robert and Hsi. Pearson's correlation coefficient (R) was used to assess the relationships between the monthly population fluctuations and meteorological variables. RESULTS: Overall, 23750 mosquitoes belonging to four genera and nineteen species were collected and identified. The highest population density of mosquitoes was in July and the lowest in May. The ISA/SISA indices for Culex pipiens were both 1 for larvae and 1.25/0.973 for adults in total catch performed in human dwellings. For Cx. tritaeniorhynchus, the ISA/SISA were 1.68/0.938 in pit shelter method. A significant positive correlation was observed between population fluctuations of Cx. tritaeniorhynchus and mean temperature (R: 0.766, P< 0.027). CONCLUSION: The results indicated that the mosquitoes are more active in July, and Cx. pipiens and Cx. tritaeniorhynchus were the most abundant species. Considering the potential of these species as vectors of numerous pathogens, control programs can be planed based on their monthly activity pattern in the area.

A multivariate geostatistical framework for combining multiple indices of abundance for disease vectors and reservoirs: a case study of rattiness in a low-income urban Brazilian community.

A key requirement in studies of endemic vector-borne or zoonotic disease is an estimate of the spatial variation in vector or reservoir host abundance. For many vector species, multiple indices of abundance are available, but current approaches to choosing between or combining these indices do not fully exploit the potential inferential benefits that might accrue from modelling their joint spatial distribution. Here, we develop a class of multivariate generalized linear geostatistical models for multiple indices of abundance. We illustrate this novel methodology with a case study on Norway rats in a low-income urban Brazilian community, where rat abundance is a likely risk factor for human leptospirosis. We combine three indices of rat abundance to draw predictive inferences on a spatially continuous latent process, rattiness, that acts as a proxy for abundance. We show how to explore the association between rattiness and spatially varying environmental factors, evaluate the relative importance of each of the three contributing indices and assess the presence of residual, unexplained spatial variation, and identify rattiness hotspots. The proposed methodology is applicable more generally as a tool for understanding the role of vector or reservoir host abundance in predicting spatial variation in the risk of human disease.

Assessing migration patterns in Passerina ciris using the world's bird collections as an aggregated resource.

Natural history museum collections (NHCs) represent a rich and largely untapped source of data on demography and population movements. NHC specimen records can be corrected to a crude measure of collecting effort and reflect relative population densities with a method known as abundance indices. We plotted abundance index values from georeferenced NHC data in a 12-month series for the new world migratory passerine Passerina ciris across its molting and wintering range in Mexico and Central America. We illustrated a statistically significant change in abundance index values across regions and months that suggests a quasi-circular movement around its non-breeding range, and used enhanced vegetation index (EVI) analysis of remote sensing plots to demonstrate non-random association of specimen record abundance with areas of high primary productivity. We demonstrated how abundance indices from NHC specimen records can be applied to infer previously unknown migratory behavior, and be integrated with remote sensing data to provide a deeper understanding of demography and behavioral ecology across time and space.