Re-emerging Infectious Disease Research Articles

Molecular and Serological Prevalence of Leptospira spp. in Feral Pigs (Sus scrofa) and their Habitats in Alabama, USA.

Leptospirosis is a widespread zoonosis and has been recognized as a re-emerging infectious disease in humans and a variety of wild and domestic animal species. In order to understand the prevalence and diversity of Leptospira spp. in feral pig populations of Alabama, we trapped 315 feral pigs in Bullock County east-central Alabama, and collected 97 environmental samples from riparian areas in Bullock County and Macon County east-central Alabama. Two previously published PCRs followed by DNA sequencing and BLASTn were performed to identify pathogenic Leptospira species in the kidney of feral pigs (3.2%, 10/315) as well as environmental samples collected from the habitats of feral pigs (2.1%, 2/97), but not in the whole blood samples (n = 276) or spleen (n = 51). An ELISA determined that 44.2% of serum samples (122/276) were antibody-positive for Leptospira. The identification of two pathogenic Leptospira species from environmental samples and the high sero-positivity in feral pigs suggests potential pathogen shedding from feral pigs to environments, and to humans and domestic animals. In order to better understand the risk to human health associated with feral swine presence, further studies are warranted to explore the interrelationship between Leptospira spp. shedding in the urine of feral pigs and bacterial culture to explore pathogenicity. Multi-locus sequencing typing (MLST) and microscopic agglutination tests (MAT) should be performed in future studies to make a definite determination of pathogenic Leptospira in feral pigs in Alabama.

Usability and the Rapid Deployable Infectious Disease Decision Support System.

Health information technology-guided clinical decision support has demonstrated decreases in patient safety errors in the electronic health record. Unknown and re-emerging infectious diseases are a growing concern for many healthcare facilities. The purpose of this project was to develop a modular approach to integrate rapid deployment of clinical decision support for infectious diseases into the clinical workflow and evaluate the usability of the design. This article reports on the results of a quality improvement project to develop, implement, and evaluate rapid deployment of a clinical decision support module using a tuberculosis use case. Important lessons learned from the electronic health record build with previous Ebola and Zika decision support alert strategy are discussed as foundational in guiding the overall design, implementation, and evaluation of improvement strategies. Subject matter expert feedback was sought throughout the project for electronic health record design and build considerations. Usability evaluation was conducted using the classic Task, User, Representation, and Function unified framework of electronic health record usability. Usability satisfaction for both providers and nurses remained high. Tuberculosis cases pre-alert and post-alert had decreased order times for diagnostic studies. Results suggest satisfied clinicians coupled with usable systems create a more efficient workflow resulting in safer and timelier diagnostic testing.

These Are the Genes You're Looking For: Finding Host Resistance Genes.

Humanity's ongoing struggle with new, re-emerging and endemic infectious diseases serves as a frequent reminder of the need to understand host-pathogen interactions. Recent advances in genomics have dramatically advanced our understanding of how genetics contributes to host resistance or susceptibility to bacterial infection. Here we discuss current trends in defining host-bacterial interactions at the genome-wide level, including screens that harness CRISPR/Cas9 genome editing, natural genetic variation, proteomics, and transcriptomics. We report on the merits, limitations, and findings of these innovative screens and discuss their complementary nature. Finally, we speculate on future innovation as we continue to progress through the postgenomic era and towards deeper mechanistic insight and clinical applications.

Tularemia: a re-emerging tick-borne infectious disease.

Tularemia is a bacterial disease of humans, wild, and domestic animals. Francisella tularensis, which is a Gram-negative coccobacillus-shaped bacterium, is the causative agent of tularemia. Recently, an increase in the number of human tularemia cases has been noticed in several countries around the world. It has been reported mostly from North America, several Scandinavian countries, and certain Asian countries. The disease spreads through vectors such as mosquitoes, horseflies, deer flies, and ticks. Humans can acquire the disease through direct contact of sick animals, consumption of infected animals, drinking or direct contact of contaminated water, and inhalation of bacteria-loaded aerosols. Low infectious dose, aerosol route of infection, and its ability to induce fatal disease make it a potential agent of biological warfare. Tularemia leads to several clinical forms, such as glandular, ulceroglandular, oculoglandular, oropharyngeal, respiratory, and typhoidal forms. The disease is diagnosed through the use of culture, serology, or molecular methods. Quinolones, tetracyclines, or aminoglycosides are frequently used in the treatment of tularemia. No licensed vaccine is available in the prophylaxis of tularemia and this is need of the time and high-priority research area. This review mostly focuses on general features, importance, current status, and preventive measures of this disease.

A computational framework for modeling and studying pertussis epidemiology and vaccination

BackgroundEmerging and re-emerging infectious diseases such as Zika, SARS, ncovid19 and Pertussis, pose a compelling challenge for epidemiologists due to their significant impact on global public health. In this context, computational models and computer simulations are one of the available research tools that epidemiologists can exploit to better understand the spreading characteristics of these diseases and to decide on vaccination policies, human interaction controls, and other social measures to counter, mitigate or simply delay the spread of the infectious diseases. Nevertheless, the construction of mathematical models for these diseases and their solutions remain a challenging tasks due to the fact that little effort has been devoted to the definition of a general framework easily accessible even by researchers without advanced modelling and mathematical skills.ResultsIn this paper we describe a new general modeling framework to study epidemiological systems, whose novelties and strengths are: (1) the use of a graphical formalism to simplify the model creation phase; (2) the implementation of an R package providing a friendly interface to access the analysis techniques implemented in the framework; (3) a high level of portability and reproducibility granted by the containerization of all analysis techniques implemented in the framework; (4) a well-defined schema and related infrastructure to allow users to easily integrate their own analysis workflow in the framework. Then, the effectiveness of this framework is showed through a case of study in which we investigate the pertussis epidemiology in Italy.ConclusionsWe propose a new general modeling framework for the analysis of epidemiological systems, which exploits Petri Net graphical formalism, R environment, and Docker containerization to derive a tool easily accessible by any researcher even without advanced mathematical and computational skills. Moreover, the framework was implemented following the guidelines defined by Reproducible Bioinformatics Project so it guarantees reproducible analysis and makes simple the developed of new user-defined workflows.

Recent advances and challenges in electrochemical biosensors for emerging and re-emerging infectious diseases

The rise of emerging infectious diseases (EIDs) as well as the increase in spread of existing infections is threatening global economies and human lives, with several countries still fighting repeated onslaught of a few of these epidemics. The catastrophic impact a pandemic has on humans and economy should serve as a reminder to be better prepared to the advent of known and unknown pathogens in the future. The goal of having a set of initiatives and procedures to tackle them is the need of the hour.Rapid detection and point-of-care (POC) analysis of pathogens causing these diseases is not only a problem entailing the scientific community but also raises challenges in tailoring appropriate treatment strategies to the healthcare sector. Among the various methods used to detect pathogens, Electrochemical Biosensor Technology is at the forefront in the development of POC devices. Electrochemical Biosensors stand in good stead due to their rapid response, high sensitivity and selectivity and ease of miniaturization to name a few advantages.This review explores the innovations in electrochemical biosensing based on the various electroanalytical techniques including voltammetry, impedance, amperometry and potentiometry and discusses their potential in diagnosis of emerging and re-emerging infectious diseases (Re-EIDs), which are potential pandemic threats.

Diagnosis of scrub typhus: recent advancements and challenges.

Scrub typhus is a mite-borne, acute febrile illness caused by the bacterium Orientia tsutsugamushi. It is a re-emerging infectious disease of the tsutsugamushi triangle. Scrub typhus is transmitted through bites of contaminated chiggers (larval stage). Diagnosis of scrub typhus is challenging as its symptoms mimic with other acute febrile illnesses. Several methods are effectual for diagnosis of scrub typhus that includes enzyme-linked immunosorbent assay (ELISA), immunofluorescence assay (IFA), immunochromatographic test (ICT), Weil–Felix, polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP). Weil–Felix test was initially used for the diagnosis of scrub typhus in underdeveloped countries but not preferred due to a lack of both specificity and sensitivity. Other immuno-based methods like IFA and ELISA are most outrank for detection of scrub typhus due to their higher sensitivity and specificity, but not vigorous to lay bare the infection at early stages and need the convalescent sampling for verification of positive samples. On another deed, PCR based methods becoming acceptable over era due to its dexterity of early-stage diagnosis with higher specificity and sensitivity but lack its applicability in circumstances of scrub typhus due to the variegated genetic makeup of Orientia tsutsugamushi among its serotypes. The present review focused on various detection methods along with their advantages and disadvantages used in the diagnosis of scrub typhus. A comparison between available methods of diagnosis with challenges in the detection of scrub typhus is also summarized.

Detection of Emerging Infectious Disease in Cynopterus brachyotis and Rhinolopus boorneensis as Reservoirs of Zoonotic Diseases in Indonesia

Bats are mammal species that have the highest diversity. During the last two decades, various types of infections caused by microorganisms have again become epidemic in many countries, this phenomenon is known as a new infectious disease that arises and re-emerges or Re-Emerging Infectious Diseases (EID/ REID). The purpose of this study was to identify EID in bats in the karst area of South Malang. The research method of bat sampling is conducted in the karst area of South Malang, bats are identified by species, taken by blood, prepared and carried out by NGS (next generation sequencing). From the results of the research conducted, obtained 2 types of bats namely fruit-eating bats (Chiroptera brachjatis) and insect bats (Rhinolopus boorneensis). From the results of the NGS, we get specific viruses and bacteria in bats. The conclusion of this research is that bat in South Malang Karst has potential as a carrier of EID and zoonotic disease.

First Prototype of the Infectious Diseases Seeker (IDS) Software for Prompt Identification of Infectious Diseases

The rapid detection of ongoing outbreak — and the identification of causative pathogen — is pivotal for the early recognition of public health threats. The emergence and re-emergence of infectious diseases are linked to several determinants, both human factors — such as population density, travel, and trade — and ecological factors — like climate change and agricultural practices. Several technologies are available for the rapid molecular identification of pathogens [e.g. real-time polymerase chain reaction (PCR)], and together with on line monitoring tools of infectious disease activity and behaviour, they contribute to the surveillance system for infectious diseases. Web-based surveillance tools, infectious diseases modelling and epidemic intelligence methods represent crucial components for timely outbreak detection and rapid risk assessment. The study aims to integrate the current prevention and control system with a prediction tool for infectious diseases, based on regression analysis, to support decision makers, health care workers, and first responders to quickly and properly recognise an outbreak. This study has the intention to develop an infectious disease regressive prediction tool working with an off-line database built with specific epidemiological parameters of a set of infectious diseases of high consequences. The tool has been developed as a first prototype of a software solution called Infectious Diseases Seeker (IDS) and it had been established in two main steps, the database building stage and the software implementation stage (MATLAB® environment). The IDS has been tested with the epidemiological data of three outbreaks occurred recently: severe acute respiratory syndrome epidemic in China (2002–2003), plague outbreak in Madagascar (2017) and the Ebola virus disease outbreak in the Democratic Republic of Congo (2018). The outcomes are promising and they reveal that the software has been able to recognize and characterize these outbreaks. The future perspective about this software regards the developing of that tool as a useful and user-friendly predictive tool appropriate for first responders, health care workers, and public health decision makers to help them in predicting, assessing and contrasting outbreaks.

Biosafety and biosecurity approaches to restrain/contain and counter SARS-CoV-2/COVID-19 pandemic: a rapid-review.

Emergence and reemergence of infectious diseases pose significant public health risks that are continuously haunting human civilization in the past several decades. Such emerging pathogens should be considered as a high threat to humans, animals, and environmental health. The year 2020 was welcomed by another significant virus from family Coronaviridae called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the coronavirus disease 2019 (COVID-19). The disease was first reported in the city of Wuhan, Hubei province, China. Within a short time, this disease attained the status of the Public Health Emergency of International Concern. Presently, COVID-19 has spread to more than 150 countries, therefore, the World Health Organization (WHO) called it a pandemic. The Chinese government, along with WHO, other health agencies, and many nations, are monitoring the current situation closely to analyze the impact of SARS-CoV-2/COVID-19 on humans, animals, and environmental health. In the context of the current situation, biosafety and biosecurity measure that focus on One Health aspects of the disease outbreaks and the SARS-CoV-2 spread are of great importance to restrain this pathogen. Along with these efforts, standard precaution and control measures should also be taken at personal and community level to prevent the spreading of any contagion diseases, including COVID-19. Researchers are putting their very high efforts to develop suitable vaccines and therapeutics/drugs to combat COVID-19. This review aims to highlight the importance of biosafety, biosecurity, One Health approach, and focusing on recent developments and the ways forward to prevent and control COVID-19 in a useful way.

The zoonotic pathogen Leptospira interrogans mitigates environmental stress through cyclic-di-GMP-controlled biofilm production

The zoonotic bacterium Leptospira interrogans is the aetiological agent of leptospirosis, a re-emerging infectious disease that is a growing public health concern. Most human cases of leptospirosis result from environmental infection. Biofilm formation and its contribution to the persistence of virulent leptospires in the environment or in the host have scarcely been addressed. Here, we examined spatial and time-domain changes in biofilm production by L. interrogans. Our observations showed that biofilm formation in L. interrogans is a highly dynamic process and leads to a polarized architecture. We notably found that the biofilm matrix is composed of extracellular DNA, which enhances the biofilm’s cohesiveness. By studying L. interrogans mutants with defective diguanylate cyclase and phosphodiesterase genes, we show that biofilm production is regulated by intracellular levels of bis-(3′–5′)-cyclic dimeric guanosine monophosphate (c-di-GMP) and underpins the bacterium’s ability to withstand a wide variety of simulated environmental stresses. Our present results show how the c-di-GMP pathway regulates biofilm formation by L. interrogans, provide insights into the environmental persistence of L. interrogans and, more generally, highlight leptospirosis as an environment-borne threat to human health.

Dynamical footprints enable detection of disease emergence.

Developing methods for anticipating the emergence or reemergence of infectious diseases is both important and timely; however, traditional model-based approaches are stymied by uncertainty surrounding the underlying drivers. Here, we demonstrate an operational, mechanism-agnostic detection algorithm for disease (re-)emergence based on early warning signals (EWSs) derived from the theory of critical slowing down. Specifically, we used computer simulations to train a supervised learning algorithm to detect the dynamical footprints of (re-)emergence present in epidemiological data. Our algorithm was then challenged to forecast the slowly manifesting, spatially replicated reemergence of mumps in England in the mid-2000s and pertussis post-1980 in the United States. Our method successfully anticipated mumps reemergence 4 years in advance, during which time mitigation efforts could have been implemented. From 1980 onwards, our model identified resurgent states with increasing accuracy, leading to reliable classification starting in 1992. Additionally, we successfully applied the detection algorithm to 2 vector-transmitted case studies, namely, outbreaks of dengue serotypes in Puerto Rico and a rapidly unfolding outbreak of plague in 2017 in Madagascar. Taken together, these findings illustrate the power of theoretically informed machine learning techniques to develop early warning systems for the (re-)emergence of infectious diseases.

PIN79 VACCINATION COVERAGE RATE: WHAT CAN WE EXPECT FROM BRAZIL?

The maintenance of high vaccine coverage rates is an important strategy for infectious disease control in the context of migration and tourism. The annual rate of vaccination coverage (ARVC) has decreased in Brazil in recent years. Our aim is to analyze historical ARVC data and forecast Brazilian performance in the next five years. We applied the Autoregressive Integrated Moving Average (ARIMA) model to the Brazilian ARVC time series from 1994 to 2018. Data were collected from the National Immunization Program and evaluated in four steps: (1) Data analysis: data were analyzed to identify stationarity, seasonal variation, level, cycle and trend; (2) Model Identification: this involved the estimation of the parameters p, d and q using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values; (3) Model checking: this step determined whether the specified model was valid based on multi-step-ahead forecasting; and (4) Forecasting: the model was tested on real data to forecast the next five years of ARVC. The data showed a growing in ARVC between 1994 and1999, random variations from 2000-2010 and irregular variations between 2011 and 2018. The largest reduction in ARVC occurred in 2016 (50.4%). The AIC automatically identified a best model with ARIMA (1, 1, 2) in software Gretl. The ARIMA (1, 1, 2) forecast showed that ARVC will increase on average by 1.53% per year and a total of 7.06% over the next 5 years to reach an ARVC of 77.07 by 2023, if no government action is taken during this period. The ARIMA model can be used for forecasting future ARVC and will help decision-makers to establish strategies for the Brazilian vaccination program. Health authorities should make every effort to reestablish ARVC greater than 90% to avoid the re-emergence of infectious diseases that were previously controlled or eliminated in Brazil.

Emergence and Re-Emergence of Infectious Diseases: Perpetual Threat to Public Health World Wide

Now-a-days emerging and re-emerging infections worldwide are becoming the utmost problem for the development of mankind. Many different infections are considered to be zoonotic for humans (transferred from animals to humans). Emerging infections are those which are completely new contagion and affected new geographical locations. Infections are thought to be re-emerging that were important health problem globally or in a specific region, then diminished and once again appear and become the health issues for vast number of population. Although, zoonotic infective agents are most probably thought to be the cause of emergence and re-emergence of communicable diseases.

Seroprevalence with Clinical Manifestations and Laboratory Profiles of Scrub Typhus Infection in Patients Attending to a Tertiary Care Hospital in Kota, South-East Rajasthan, India

Background: Scrub typhus, a zoonotic rickettsial illness, is caused by Orientia tsutsugamushi, an obligate intracellular Gram-negative bacterium. It is transmitted by the bite of larval (chiggers) trombiculid mites.Owing to frequent outbreaks witnessed in different parts of the country in the recent past, scrub typhus is being described as a re-emerging infectious disease in India. Overall mortality varies from 7 to 30%. Objectives: The objective of the present study was to evaluate serological evidence and analyze clinical manifestations and laboratory profile of scrub typhus infection in febrile patients in South-East Rajasthan. The ultimate goal of this study was to identify scrub typhus infection in early phase of disease and prevent future complications. Methodology: The present study was conducted in the central laboratory of Govt. Medical College, Kota from period of 1st January, 2018 to 31th December 2018 to evaluate the seroprevalence of scrub typhus infection in South-East Rajasthan. Sera were tested by InBiOS scrub typhus detect TM IgM ELISA system test for IgM antibody detection as per kit insert. Results: Out of total 4928 serum samples tested, 365 (7.41%) were found positive for scrub typhus infection. Of all the patients tested, 2611 (52.98%) were males and 2317 (47.02%) were females. 172 (47.12%) positive samples were of male patients and 193 (52.88%) positive samples were of female patients. Scrub typhus affected males and females in a ratio of about 1:1.1. Out of the total positive for scrub typhus, age groups mostly affected were 21-30 years, 41-50 years and 31-40 year 20.55, 16.71 and 16.16% respectively. Seasonal trend showed a gradual increase in scrub typhus positives started from August (6.85%) with a peak in September (50.14%) and October (33.70%). CONCLUSION: Scrub typhus has emerged as an important cause of febrile illness in various parts of India. There is no vaccine available for any rickettsial infections including scrub typhus. For this, rapid and accurate diagnosis becomes necessary, especially in the absence of eschars for preventing morbidity, mortality and further complications. This study thus emphasizes that in all undifferentiated fever patients who had lymphocytosis (50.14% reported in this study) and other clinical features suggest scrub typhus in endemic region; then scrub typhus should be high on card of probability. Keywords: Scrub typhus, Orientia tsutsugamushi, chiggers, trombiculid mites, ELISA, rickettsial disease Cite this Article Bhupendra Kumar Mandawat, Ghanshyam Soni, Preetam Singh Mandawat. Seroprevalence with Clinical Manifestations and Laboratory Profiles of Scrub Typhus Infection in Patients Attending to a Tertiary Care Hospital in Kota, South-East Rajasthan, India. Research & Reviews: A Journal of Microbiology & Virology. 2020; 10(1): 1–9p.

Pediculosis capitis y transmisión potencial de enfermedades infecciosas reemergentes en Colombia. Revisión de la literatura

Introducción. La infestación por piojos de la cabeza en humanos (Pediculus humanus capitis) se conoce como pediculosis capitis. Estos parásitos pueden ser vectores de enfermedades infecciosas con potencial reemergente.Objetivos. Revisar la literatura actual sobre las enfermedades infecciosas transmitidas por piojos de la cabeza y realizar una breve descripción de sus manifestaciones clínicas.Materiales y métodos. Se realizó una revisión de la literatura en PubMed, ScienceDirect, SciELO y Redalyc mediante la siguiente estrategia de búsqueda: años de publicación: 1938 a 2019; idioma: inglés y español; términos de búsqueda: “Pediculus”, “lice infestations”, “bacteria”, “emerging communicable diseases”, “Rickettsia”, “Bartonella”, “Borrelia”, “Acinetobacter”, “Yersinia“, and “Colombia”, y sus equivalentes en español.Resultados. De los 110 artículos incluidos, la mayoría correspondió a investigaciones originales (48.2%). A nivel mundial, numerosos estudios han reportado la transmisión de Rickettsia prowazekii, Bartonella quintana, Borrelia recurrentis, Staphylococcus aureus, Acinetobacter baumannii y Yersinia pestis, entre otras bacterias, por los piojos de la cabeza y del cuerpo en humanos.Conclusiones. Aunque las enfermedades infecciosas transmitidas por piojos de la cabeza son raras, guardan potencial reemergente en poblaciones afectadas por migraciones humanas, crisis sociopolíticas, indigencia e inmunosupresión. En Colombia no se han realizado investigaciones sobre la transmisión de estas enfermedades por Pediculus spp., por lo que se sugiere que en estudios futuros se determine la prevalencia y los aspectos epidemiológicos de las enfermedades transmitidas por piojos de la cabeza en población colombiana.

Extended urbanisation and the spatialities of infectious disease: Demographic change, infrastructure and governance

This paper argues that contemporary processes of extended urbanisation, which include suburbanisation, post-suburbanisation and peri-urbanisation, may result in increased vulnerability to infectious disease spread. Through a review of existing literature at the nexus of urbanisation and infectious disease, we consider how this (potential) increased vulnerability to infectious diseases in peri- or suburban areas is in fact dialectically related to socio-material transformations on the metropolitan edge. In particular, we highlight three key factors influencing the spread of infectious disease that have been identified in the literature: demographic change, infrastructure and governance. These have been chosen given both the prominence of these themes and their role in shaping the spread of disease on the urban edge. Further, we suggest how a landscape political ecology framework can be useful for examining the role of socio-ecological transformations in generating increased risk of infectious disease in peri- and suburban areas. To illustrate our arguments we will draw upon examples from various re-emerging infectious disease events and outbreaks around the world to reveal how extended urbanisation in the broadest sense has amplified the conditions necessary for the spread of infectious diseases. We thus call for future research on the spatialities of health and disease to pay attention to how variegated patterns of extended urbanisation may influence possible outbreaks and the mechanisms through which such risks can be alleviated.

A forensic evaluation of plague - a re-emerging infectious disease with biowarfare potential.

Plague is an acute infectious disease caused by the gram-negative cocco-bacillus Yersinia pestis. It has been responsible for 200 million deaths throughout history with three major pandemics. There are three forms: bubonic, septicaemic and pneumonic, each carrying a significant mortality rate. The usual transmission is from fleas carried by rodents. Recently, it has been listed as one of the reemerging infectious diseases globally, with a potential use in bioterrorism. At autopsy there may be lymphadenopathy, fulminant pneumonia or diffuse interstitial pneumonitis. However any organ may be affected with myocarditis, meningitis, pharyngitis and hepatic and splenic necrosis. The lethality of plague with the resurgence in numbers of cases, development of antibiotic resistance, recent occurrence in urban areas and the lack of a vaccine make it a disease not to be missed in the mortuary.

Leptospira infection and shedding in dogs in Thailand

BackgroundLeptospirosis is a widespread zoonosis and has been recognized as a re-emerging infectious disease in humans and dogs, but prevalence of Leptospira shedding in dogs in Thailand is unknown. The aim of this study was to determine urinary shedding of Leptospira in dogs in Thailand, to evaluate antibody prevalence by microscopic agglutination test (MAT) and enzyme-linked immunosorbent assay (ELISA), and to assess risk factors for Leptospira infection.In Northern, Northeastern, and Central Thailand, 273 stray (n = 119) or client-owned (n = 154) dogs from rural (n = 139) or urban (n = 134) areas were randomly included. Dogs that had received antibiotics within 4 weeks prior to sampling were excluded. No dog had received vaccination against Leptospira. Urine was evaluated by real-time polymerase chain reaction (PCR) specific for lipL32 gene of pathogenic Leptospira. Additionally, urine was cultured for 6 months in Ellinghausen-McCullough-Johnson-Harris (EMJH) medium. Antibodies were measured by ELISA and MAT against 24 serovars belonging to 15 serogroups and 1 undesignated serogroup. Risk factor analysis was performed with backwards stepwise selection based on Wald.ResultsTwelve of 273 (4.4%; 95% confidence interval (CI): 2.0–6.8%) urine samples were PCR-positive. In 1/273 dogs (0.4%; 95% CI: 0.01–1.1%) Leptospira could be cultured from urine. MAT detected antibodies in 33/273 dogs (12.1%; 95% CI: 8.2–16.0%) against 19 different serovars (Anhoa, Australis, Ballum, Bataviae, Bratislava, Broomi, Canicola, Copenhageni, Coxi, Grippotyphosa, Haemolytica, Icterohaemorrhagiae, Khorat, Paidjan, Patoc, Pyrogenes, Rachmati, Saxkoebing, Sejroe). In 111/252 dogs (44.0%; 95% CI: 37.9–50.2%) immunoglobulin M (IgM) and/or immunoglobulin G (IgG) antibodies were found by ELISA. Female dogs had a significantly higher risk for Leptospira infection (p = 0.023).ConclusionsLeptospira shedding occurs in randomly sampled dogs in Thailand, with infection rates comparable to those of Europe and the USA. Therefore, the potential zoonotic risk should not be underestimated and use of Leptospira vaccines are recommended.

Detecting critical slowing down in high-dimensional epidemiological systems.

Despite medical advances, the emergence and re-emergence of infectious diseases continue to pose a public health threat. Low-dimensional epidemiological models predict that epidemic transitions are preceded by the phenomenon of critical slowing down (CSD). This has raised the possibility of anticipating disease (re-)emergence using CSD-based early-warning signals (EWS), which are statistical moments estimated from time series data. For EWS to be useful at detecting future (re-)emergence, CSD needs to be a generic (model-independent) feature of epidemiological dynamics irrespective of system complexity. Currently, it is unclear whether the predictions of CSD—derived from simple, low-dimensional systems—pertain to real systems, which are high-dimensional. To assess the generality of CSD, we carried out a simulation study of a hierarchy of models, with increasing structural complexity and dimensionality, for a measles-like infectious disease. Our five models included: i) a nonseasonal homogeneous Susceptible-Exposed-Infectious-Recovered (SEIR) model, ii) a homogeneous SEIR model with seasonality in transmission, iii) an age-structured SEIR model, iv) a multiplex network-based model (Mplex) and v) an agent-based simulator (FRED). All models were parameterised to have a herd-immunity immunization threshold of around 90% coverage, and underwent a linear decrease in vaccine uptake, from 92% to 70% over 15 years. We found evidence of CSD prior to disease re-emergence in all models. We also evaluated the performance of seven EWS: the autocorrelation, coefficient of variation, index of dispersion, kurtosis, mean, skewness, variance. Performance was scored using the Area Under the ROC Curve (AUC) statistic. The best performing EWS were the mean and variance, with AUC > 0.75 one year before the estimated transition time. These two, along with the autocorrelation and index of dispersion, are promising candidate EWS for detecting disease emergence.