Predicting the Presence of Leptospires in Rodents from Environmental Indicators Opens Up Opportunities for Environmental Monitoring of Human Leptospirosis

First Molecular Detection of Pathogens Leptospira in Common Rodent Captured in North Algeria Urban Areas

Leptospirosis is an anthropozoonosis disease of worldwide distribution caused by mobile spirochetes of the genus Leptospira and rodents, mainly rats, are described as its primary reservoir. In Algeria, there is limited data about the prevalence of Leptospira spp. in humans and animals, as well as Leptospira carriage in wild rodents. The study aimed to highlight the importance of rodents as a reservoir of Leptospira bacterium in Blida city in Algeria by detecting and identifying circulating Leptospira species in the rodent population. A total of 101 rodents, 95 Rattus Norvegicus, 5 Rattus Rattus, and 1 Mus Musculus were captured and tested for pathogenic Leptospira spp. byreal-time PCR targeting the Leptospira 16S rRNA (rrs) gene, revealing a total prevalence of 40.6%, 95% IC [30.9–50.8%]. Positive samples were subjected to species-specific real-time PCR assays targeting L. interrogans, L. noguchii, L. borgpetersenii, and L. kirschneri for species identification. However, positive samples for which Leptospira-species could not be determined were subjected to conventional PCR targeting the partial 16S rRNA (rrs) gene, and amplified DNA was subjected to sequencing. Leptospira spp. was detected in 36 kidney, 16 urine, and three lung specimens. L. interrogans was identified in 39 rodents and L. borpetersenii in one rodent; however, one rodent with renal carriage could not be typed due to poor DNA quality. This study provides the first description of pathogenic Leptospira spp. in wild rodents in Algeria. These findings suggest a high potential risk of leptospirosis transmission from rodents to humans and animals in Algeria and therefore imply the adoption of prophylactic measures. In addition, further studies, including different animals and rodent species, should be conducted to clarify the epidemiology of this disease in Algeria.

Seroprevalence and Molecular Characterization of Leptospira spp. in Rats Captured near Pig Farms in Colombia

Gram-negative spirochete Leptospira spp. causes leptospirosis. Leptospirosis is still a neglected disease, even though it can cause potentially fatal infections in a variety of species including humans. The purpose of this study was to determine the seroprevalence of leptospirosis in pig farm captured rodents and characterize the isolated samples. Rats were captured, sampled, and euthanized in the vicinity of pig farms to obtain serum for microagglutination tests (MAT) and kidney tissues for PCR amplification of the 16S rRNA and LipL32 genes. A fraction of the 16S rRNA PCR product was sequenced and phylogenetically analyzed. The results showed a Leptospira seroprevalence of 13.8% (77/555) among the 555 captured rats. PCR positivity for Leptospira spp. reached 31.2% (156/500), and the positivity for pathogenic Leptospira spp. was 4% (22/500). Phylogenetic analysis matched eight samples with L. interrogans serovar icterohaemorrhagiae and two with L. interrogans serovar pyrogenes. Two sequences were located within the pathogenic Leptospira clade but did not match with any specific strain. The seroprevalence found in the rats around swine farms indicates a potential risk of transmission to the pigs. The identification of pathogenic Leptospira outlines the importance of more research as well as updating the current strategies for the diagnosis, control, and prevention of porcine leptospirosis in Colombia.

Using Remote Sensing Data and Species–Environmental Matching Model to Predict the Potential Distribution of Grassland Rodents in the Northern China

An increase in grassland rodent pests in China has seriously affected grassland ecological environments and the development of husbandry. Here, we used remote sensing data and a species–environmental matching model to predict the potential spatial distribution of the five major rodent pest species (Microtus, Citellus, Myospalax, Meriones, Ochotona) in northern China, and examined how the predicted suitability of the area depends on environmental variables. The results were consistent and significant, better than random, and close to optimal. Meriones and Microtus had the largest areas of High Suitability and Moderate Suitability with regard to environmental conditions. The combination analysis of areas of Moderate Suitability and High Suitability showed that for 66% of the total area, conditions were suitable for just one rodent species, while conditions suitable for two and three kinds of rodents accounted for 31% and 3%, respectively. Altitude, land surface temperature in winter (November, December, February) and summer (May, June, July), vegetation cover in summer (July, August), and precipitation from spring to summer (April, May, June) determined the spatial distribution of grassland rodents. Our findings provide a powerful and useful methodological tool for tracking the five major rodent pest species in northern China and for future management measures to ensure grassland ecological environment security.

Eco-epidemiological scaling of Leptospirosis: Vulnerability mapping and early warning forecasts

Infectious disease epidemics are plaguing the world and a lot of research is focused on the development of models to reproduce disease dynamics for eco-environmental and biological investigation, and disease management. Leptospirosis is an example of a neglected zoonosis strongly mediated by ecohydrological dynamics with emerging endemic and epidemic patterns worldwide in both animal and human populations. By accounting for large heterogeneities of affected areas we show how exponential endemics and scale-free epidemics are largely predictable and linked to common socio-environmental features via scaling laws with different exponents that inform about vulnerability factors. This led to the development of a novel pattern-oriented integrated model that can be used as an early-warning signal (EWS) tool for endemic-epidemic regime classification, risk determinant attribution, and near real-time forecast of outbreaks. Forecasts are grounded on expected outbreak recurrence time dependent on exceedance probabilities and statistical EWS that sense outbreak onset. A stochastic spatially-explicit model is shown to comprehensively predict outbreak dynamics (early sensing, timing, magnitude, decay, and eco-environmental determinants) and derive a spreading factor characterizing endemics and epidemics, where average over maximum rainfall is the critical factor characterizing disease transitions. Dynamically, case cross-correlation considering neighboring communities senses 2-weeks in advance outbreaks. Eco-environmental scaling relationships highlight how predicted host suitability and topographic index can be used as epidemiological footprints to effectively distinguish and control Leptospirosis regimes and areas dependent on hydro-climatological dynamics as the main trigger. The spatio-temporal scale-invariance of epidemics - underpinning persistent criticality and neutrality or independence among areas - is emphasized by the high accuracy in reproducing sequence and magnitude of cases via reliable surveillance. Further investigations of robustness and universality of eco-environmental determinants are required; nonetheless a comprehensive and computationally simple EWS method for the full characterization of Leptospirosis is provided. The tool is extendable to other climate-sensitive zoonoses to define vulnerability factors and predict outbreaks useful for optimal disease risk prevention and control.