A High-Resolution Earth Observations and Machine Learning-Based Approach to Forecast Waterborne Disease Risk in Post-Disaster Settings

Responding to infrastructural damage in the aftermath of natural disasters at a national, regional, and local level poses a significant challenge. Damage to road networks, clean water supply, and sanitation infrastructures, as well as social amenities like schools and hospitals, exacerbates the circumstances. As safe water sources are destroyed or mixed with contaminated water during a disaster, the risk of a waterborne disease outbreak is elevated in those disaster-affected locations. A country such as Haiti, where a large quantity of the population is deprived of safe water and basic sanitation facilities, would suffer more in post-disaster scenarios. Early warning of waterborne diseases like cholera would be of great help for humanitarian aid, and the management of disease outbreak perspectives. The challenging task in disease forecasting is to identify the suitable variables that would better predict a potential outbreak. In this study, we developed five (5) models including a machine learning approach, to identify and determine the impact of the environmental and social variables that play a significant role in post-disaster cholera outbreaks. We implemented the model setup with cholera outbreak data in Haiti after the landfall of Hurricane Matthew in October 2016. Our results demonstrate that adding high-resolution data in combination with appropriate social and environmental variables is helpful for better cholera forecasting in a post-disaster scenario. In addition, using a machine learning approach in combination with existing statistical or mechanistic models provides important insights into the selection of variables and identification of cholera risk hotspots, which can address the shortcomings of existing approaches

Borrelia miyamotoi

Borrelia miyamotoi sensu lato, a relapsing fever Borrelia sp., is transmitted by the same ticks that transmit B. burgdorferi (the Lyme disease pathogen) and occurs in all Lyme disease–endemic areas of the United States. To determine the seroprevalence of IgG against B. miyamotoi sensu lato in the northeastern United States and assess whether serum from B. miyamotoi sensu lato–infected persons is reactive to B. burgdorferi antigens, we tested archived serum samples from area residents during 1991–2012. Of 639 samples from healthy persons, 25 were positive for B. miyamotoi sensu lato and 60 for B. burgdorferi. Samples from ≈10% of B. miyamotoi sensu lato–seropositive persons without a recent history of Lyme disease were seropositive for B. burgdorferi. Our resultsA suggest thatA human B. miyamotoiA sensu latoA infection may be common in southern New England and that B. burgdorferi antibody testing is not an effective surrogate for detecting B. miyamotoi sensu lato infection

A new Borrelia on the block: Borrelia miyamotoi – a human health risk?

Background Borrelia miyamotoi clusters phylogenetically among relapsing fever borreliae, but is transmitted by hard ticks. Recent recognition as a human pathogen has intensified research into its ecology and pathogenic potential. Aims We aimed to provide a timely critical integrative evaluation of our knowledge on B. miyamotoi, to assess its public health relevance and guide future research. Methods This narrative review used peer-reviewed literature in English from January 1994 to December 2018. Results Borrelia miyamotoi occurs in the world’s northern hemisphere where it co-circulates with B. burgdorferi sensu lato, which causes Lyme disease. The two borreliae have overlapping vertebrate and tick hosts. While ticks serve as vectors for both species, they are also reservoirs for B. miyamotoi. Three B. miyamotoi genotypes are described, but further diversity is being recognised. The lack of sufficient cultivable isolates and vertebrate models compromise investigation of human infection and its consequences. Our understanding mainly originates from limited case series. In these, human infections mostly present as influenza-like illness, with relapsing fever in sporadic cases and neurological disease reported in immunocompromised patients. Unspecific clinical presentation, also occasionally resulting from Lyme- or other co-infections, complicates diagnosis, likely contributing to under-reporting. Diagnostics mainly employ PCR and serology. Borrelia miyamotoi infections are treated with antimicrobials according to regimes used for Lyme disease. Conclusions With co-infection of tick-borne pathogens being commonplace, diagnostic improvements remain important. Developing in vivo models might allow more insight into human pathogenesis. Continued ecological and human case studies are key to better epidemiological understanding, guiding intervention strategies

Tick-pathogen interactions and vector competence: Identification of molecular drivers for tick-borne diseases

Ticks and the pathogens they transmit constitute a growing burden for human and animal health worldwide. Vector competence is a component of vectorial capacity and depends on genetic determinants affecting the ability of a vector to transmit a pathogen. These determinants affect traits such as tick-host-pathogen and susceptibility to pathogen infection. Therefore, the elucidation of the mechanisms involved in tick-pathogen interactions that affect vector competence is essential for the identification of molecular drivers for tick-borne diseases. In this review, we provide a comprehensive overview of tick-pathogen molecular interactions for bacteria, viruses, and protozoa affecting human and animal health. Additionally, the impact of tick microbiome on these interactions was considered. Results show that different pathogens evolved similar strategies such as manipulation of the immune response to infect vectors and facilitate multiplication and transmission. Furthermore, some of these strategies may be used by pathogens to infect both tick and mammalian hosts. Identification of interactions that promote tick survival, spread, and pathogen transmission provides the opportunity to disrupt these interactions and lead to a reduction in tick burden and the prevalence of tick-borne diseases. Targeting some of the similar mechanisms used by the pathogens for infection and transmission by ticks may assist in development of preventative strategies against multiple tick-borne diseases.Peer reviewedVeterinary Pathobiolog

Raccoon Acclimation Towards Traps and its Effect on Surveillance and Monitoring of Zoonotic Diseases

Raccoons (Procyon lotor) serve as a source of infection with various pathogens for people, most notably, rabies. Raccoons are specifically targeted for the control of rabies in the United States, primarily due to the 100% fatality rate in humans and animals. There is no cure or treatment for rabies and vaccines may be administered to people if it is administered promptly. In order to evaluate how successful trapping of raccoons is by using conventional methods, motion sensing cameras were placed on traps in order to captured raccoon behaviors. Pictures were coded based on these behaviors (around the trap but not entering, entering the trap but not being caught, captured, etc) and analyzed. The first hypothesis proposed that raccoons required a period of time to become adjusted to traps placed in their environment; this hypothesis could not be accepted. The second hypothesis suggested that raccoons exhibit a trap-prone behavior, this hypothesis was accepted. These results will help in designing more successful surveillance methods for zoonotic infectious disease programs

Colpodella spp.–like Parasite Infection in Woman, China

The phylum Apicomplexa comprises intracellular protozoa that include many human pathogens. Their nearest relatives are chromerids and colpodellids. We report a case of a Babesia spp.–like relapsing infection caused by a newly described microorganism related to the Apicomplexa. This case is highly suggestive of a previously undescribed type of colpodellid that infects vertebrates