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Upcoming vaccination efforts against typhoid fever require an assessment of the baseline burden of disease in countries at risk. There are no typhoid incidence data from most low- and middle-income countries (LMICs), so model-based estimates offer insights for decision-makers in the absence of readily available data. We developed a mixed-effects model fit to data from 32 population-based studies of typhoid incidence in 22 locations in 14 countries. We tested the contribution of economic and environmental indices for predicting typhoid incidence using a stochastic search variable selection algorithm. We performed out-of-sample validation to assess the predictive performance of the model. We estimated that 17.8 million cases of typhoid fever occur each year in LMICs (95% credible interval: 6.9-48.4 million). Central Africa was predicted to experience the highest incidence of typhoid, followed by select countries in Central, South, and Southeast Asia. Incidence typically peaked in the 2-4 year old age group. Models incorporating widely available economic and environmental indicators were found to describe incidence better than null models. Recent estimates of typhoid burden may under-estimate the number of cases and magnitude of uncertainty in typhoid incidence. Our analysis permits prediction of overall as well as age-specific incidence of typhoid fever in LMICs, and incorporates uncertainty around the model structure and estimates of the predictors. Future studies are needed to further validate and refine model predictions and better understand year-to-year variation in cases.

As whole-genome sequencing capacity becomes increasingly decentralized, there is a growing opportunity for collaboration and the sharing of surveillance data within and between countries to inform typhoid control policies. This vision requires free, community-driven tools that facilitate access to genomic data for public health on a global scale. Here we present the Pathogenwatch scheme for Salmonella enterica serovar Typhi ( S . Typhi), a web application enabling the rapid identification of genomic markers of antimicrobial resistance (AMR) and contextualization with public genomic data. We show that the clustering of S . Typhi genomes in Pathogenwatch is comparable to established bioinformatics methods, and that genomic predictions of AMR are highly concordant with phenotypic susceptibility data. We demonstrate the public health utility of Pathogenwatch with examples selected from >4,300 public genomes available in the application. Pathogenwatch provides an intuitive entry point to monitor of the emergence and spread of S . Typhi high risk clones. Whole genome sequencing data are increasingly becoming routinely available but generating actionable insights is challenging. Here, the authors describe Pathogenwatch, a web tool for genomic surveillance of S. Typhi, and demonstrate its use for antimicrobial resistance assignment and strain risk assessment.

Antimicrobial resistance (AMR) is a growing public health crisis that requires innovative solutions. Current susceptibility testing approaches limit our ability to rapidly distinguish between antimicrobial-susceptible and -resistant organisms. Salmonella Typhimurium ( S . Typhimurium) is an enteric pathogen responsible for severe gastrointestinal illness and invasive disease. Despite widespread resistance, ciprofloxacin remains a common treatment for Salmonella infections, particularly in lower-resource settings, where the drug is given empirically. Here, we exploit high-content imaging to generate deep phenotyping of S . Typhimurium isolates longitudinally exposed to increasing concentrations of ciprofloxacin. We apply machine learning algorithms to the imaging data and demonstrate that individual isolates display distinct growth and morphological characteristics that cluster by time point and susceptibility to ciprofloxacin, which occur independently of ciprofloxacin exposure. Using a further set of S . Typhimurium clinical isolates, we find that machine learning classifiers can accurately predict ciprofloxacin susceptibility without exposure to it or any prior knowledge of resistance phenotype. These results demonstrate the principle of using high-content imaging with machine learning algorithms to predict drug susceptibility of clinical bacterial isolates. This technique may be an important tool in understanding the morphological impact of antimicrobials on the bacterial cell to identify drugs with new modes of action. In this work, authors combine high resolution imaging and machine learning to infer drug susceptibility in the absence of antimicrobial exposure, with the goal of their method to be transposed to diagnostics and study of the impact of any perturbation on bacterial cells.

Understanding the local burden and epidemiology of infectious diseases is crucial to guide public health policy and prioritize interventions. Typically, infectious disease surveillance relies on capturing clinical cases within a healthcare system, classifying cases by etiology and enumerating cases over a period of time. Disease burden is often then extrapolated to the general population. Serology (i.e., examining serum for the presence of pathogen-specific antibodies) has long been used to inform about individuals past exposure and immunity to specific pathogens. However, it has been underutilized as a tool to evaluate the infectious disease burden landscape at the population level and guide public health decisions. In this review, we outline how serology provides a powerful tool to complement case-based surveillance for determining disease burden and epidemiology of infectious diseases, highlighting its benefits and limitations. We describe the current serology-based technologies and illustrate their use with examples from both the pre- and post- COVID-19-pandemic context. In particular, we review the challenges to and opportunities in implementing serological surveillance in low- and middle-income countries (LMICs), which bear the brunt of the global infectious disease burden. Finally, we discuss the relevance of serology data for public health decision-making and describe scenarios in which this data could be used, either independently or in conjunction with case-based surveillance. We conclude that public health systems would greatly benefit from the inclusion of serology to supplement and strengthen existing case-based infectious disease surveillance strategies.

The interaction between schistosomiasis and Salmonella is a particularly important issue in Africa, where dual infection by the parasite and the bacterium are likely common. In this review, the ways in which schistosomiasis affects human biology as it relates to Salmonella are described. Those who are infected by both organisms experience reduced immunological functioning, exhibit irreversible organ damage due to prolonged schistosomiasis infection, and become latent carriers of Salmonella enterica serotypes Typhi and Paratyphi and S. Typhimurium. The sequestration of the bacteria in the parasite leads to ineffective antibiotic treatment because the bacteria cannot be completely killed, and lingering infection may then lead to antimicrobial resistance. These manifestations are likely not just for those dually infected but also for those first infected with schistosomes and, later, Salmonella. More data are needed to better understand dual infection, particularly as it may impact treatment and prevention of schistosomiasis and Salmonella in sub-Saharan Africa.

Typhoid fever is an acute systemic infectious disease responsible for an estimated 12–20 million illnesses and over 150 000 deaths annually. In March, 2018, a new recommendation was issued by WHO for the programmatic use of typhoid conjugate vaccines in endemic countries. Health economic analyses of typhoid vaccines have informed funding decisions and national policies regarding vaccine rollout. However, by focusing only on averted typhoid cases and their associated costs, traditional cost-effectiveness analyses might underestimate crucial benefits of typhoid vaccination programmes, because the potential effect of typhoid vaccines on the treatment of patients with non-specific acute febrile illnesses is not considered. For every true case of typhoid fever, three to 25 patients without typhoid disease are treated with antimicrobials unnecessarily, conservatively amounting to more than 50 million prescriptions per year. Antimicrobials for suspected typhoid might therefore be an important selective pressure for the emergence and spread of antimicrobial resistance globally. We propose that large-scale, more aggressive typhoid vaccination programmes—including catch-up campaigns in children up to 15 years of age, and vaccination in lower incidence settings—have the potential to reduce the overuse of antimicrobials and thereby reduce antimicrobial resistance in many bacterial pathogens. Funding bodies and national governments must therefore consider the potential for broad reductions in antimicrobial use and resistance in decisions related to the rollout of typhoid conjugate vaccines.

The International Vaccine Institute-led CAPTURA (Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia) project delivered capacity building activities to strengthen antimicrobial resistance surveillance activities in Nepal. The CAPTURA project trained 97 laboratory personnel from 19 hospitals on the use of WHONET/BacLink software to manage microbiology data in Nepal during 2020-2021. Approximately two years later, the trainees were followed up by phone to assess implementation status and effectiveness of the training. An inductive approach was used for coding and categorization of their response, and themes were generated for analysis. Trainees from ten hospitals agreed to respond regarding their experience. We found that two out of the ten hospitals were using the WHONET/BacLink software, with one each within and outside the national AMR surveillance network. The remaining eight hospitals never implemented the system despite receiving the training. Key barriers to implementation included, hospital administration prioritizing other interoperable software, limited ongoing training, inability to export data from an LIS, limited real-time assistance with technical issues, and poor confidence in analyzing data. In addition, limited human resources and minimal capacity-building activities resulted in a lack of confidence in using the system independently, which were also identified as barriers. Implementing WHONET/BacLink software in hospital settings can be challenging due to various factors, including a lack of knowledge and confidence among users, a lack of time and human resources to use the software effectively, and a lack of interoperability with other hospital management systems. Real-time support and follow-up activities potentially reinforce the skills and knowledge delivered during the training.

Rabies virus (RABV; species Lyssavirus rabies) is causing one of the oldest zoonotic diseases known to mankind, leading to fatal encephalomyelitis in animals and humans. Despite the existence of safe and effective vaccines to prevent the disease, an estimated 99% of human rabies deaths worldwide are caused by dog-mediated rabies with children at the highest risk of infection. Rabies has been endemic in Madagascar for over a century, yet there has been little research evaluating local knowledge and practices impacting on the rabies control and prevention. Thus, this study was undertaken to better understand the dog ecology including canine vaccine coverage and to assess knowledge and practices of dog owners and veterinarians. A cross-sectional study was conducted among 123 dog-owning households in thirteen fokontanys in Mahajanga from July 4 to September 13, 2016. Single and multi-member dog-owning households in the study area on the day of the interview were eligible for inclusion and purposively selected with the support of a local guide. The survey included a household questionnaire capturing information on the dog's demographics, husbandry practices, knowledge and practices towards rabies and its control measures; the dog ecology questionnaire collected dog characteristics, vaccination status and husbandry practices. All households that reported a dog bite incident, were invited to participate in a dog bite questionnaire. In addition, direct observations of roaming dogs were conducted to assess dog population demographics and to document behavioural characteristics. Two veterinarians were purposively selected and took part in an interview during the survey period, providing information on rabies control activities, including dog-care practices in the area. Descriptive and inferential data analyses were performed using Epi Info version 7.1.5.0 (CDC Atlanta, USA). We recorded a total of 400 dogs, of which 338 (84.5%) were owned amongst 123 households. More than half (67.8%) of owned dogs were between 1 to 5 years old and 95.6% were kept for guarding purposes. 45% of the surveyed dogs had free access to roam outside the premises. The majority (85.4%) of dog owners were knowledgeable that a dog bite could potentially transmit RABV to humans. 19 dog bites were reported and of these 73.6% were caused by the owner's or a neighbour's dog. In 6 of the 19 cases, children between 7 and 15 years of age were the victims. Dog vaccination coverage against rabies was 34% among owned dogs. Of the participants aware of a veterinarian, the majority (55/82) indicated that they accessed veterinarian services at irregular intervals. The main obstacles to vaccinations cited by dog owners were limited financial resources and difficulty accessing veterinary care. This study contributes to enhanced understanding of the dog ecology including canine vaccine coverage as well as knowledge and practices of dog owners in Madagascar. Most dogs in the study area were accessible for preventive vaccination through their owners, however only one third of the investigated canine population was vaccinated against rabies. Concerted national efforts towards rabies prevention and control should aim to address financial challenges and access to veterinary services.

Background Invasive non-typhoidal Salmonella (iNTS) is a growing health-concern in many parts of sub-Saharan Africa. iNTS is associated with fatal diseases such as HIV and malaria. Despite high case fatality rates, the disease has not been given much attention. The limited number of population-based surveillance studies hampers accurate estimation of global disease burden. Given the lack of available evidence on the disease, it is critical to identify high risk areas for future surveillance and to improve our understanding of iNTS endemicity. Methods Considering that population-based surveillance data were sparse, a composite index called the iNTS risk factor (iNRF) index was constructed based on risk factors that commonly exist across countries. Four risk factors associated with the prevalence of iNTS were considered: malaria, HIV, malnutrition, and safe water. The iNRF index was first generated based on the four risk factors which were collected within a 50 km radius of existing surveillance sites. Pearson product-moment correlation was used to test statistical associations between the iNRF index and the prevalence of iNTS observed in the surveillance sites. The index was then further estimated at the subnational boundary level across selected countries and used to identify high risk areas for iNTS. Results While the iNRF index in some countries was generally low (i.e. Rwanda) or high (i.e. Cote d’Ivoire), the risk-level of iNTS was variable not only by country but also within a country. At the provincial-level, the highest risk area was identified in Maniema, the Democratic Republic of Congo, whereas Dakar in Senegal was at the lowest risk. Conclusions The iNRF index can be a useful tool to understand the geographically varying risk-level of iNTS. Given that conducting a population-based surveillance study requires extensive human and financial resources, identifying high risk areas for iNTS prior to a study implementation can facilitate an appropriate site-selection process in the future.

During the coronavirus disease pandemic, we observed a 6.4-fold increase in typhoid intestinal perforation incidence in Antananarivo, Madagascar. Thirteen perforations occurred within 6 months (February 2020-July 2020), compared with 13 perforations during the previous 41 months (August 2016-January 2020). The increase may be attributable to delayed healthcare seeking during the pandemic.