Project description:Shigella sonnei is the most common agent of shigellosis in high-income countries, and causes a significant disease burden in low- and middle-income countries. Antimicrobial resistance is increasingly common in all settings. Whole genome sequencing (WGS) is increasingly utilised for S. sonnei outbreak investigation and surveillance, but comparison of data between studies and labs is challenging. Here, we present a genomic framework and genotyping scheme for S. sonnei to efficiently identify genotype and resistance determinants from WGS data. The scheme is implemented in the software package Mykrobe and tested on thousands of genomes. Applying this approach to analyse >4,000 S. sonnei isolates sequenced in public health labs in three countries identified several common genotypes associated with increased rates of ciprofloxacin resistance and azithromycin resistance, confirming intercontinental spread of highly-resistant S. sonnei clones and demonstrating the genomic framework can facilitate monitoring the spread of resistant clones, including those that have recently emerged, at local and global scales.
Project description:BackgroundThe incidence of leptospirosis, a neglected zoonotic disease, is uncertain in Tanzania and much of sub-Saharan Africa, resulting in scarce data on which to prioritize resources for public health interventions and disease control. In this study, we estimate the incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania.Methodology/principal findingsWe conducted a population-based household health care utilization survey in two districts in the Kilimanjaro Region of Tanzania and identified leptospirosis cases at two hospital-based fever sentinel surveillance sites in the Kilimanjaro Region. We used multipliers derived from the health care utilization survey and case numbers from hospital-based surveillance to calculate the incidence of leptospirosis. A total of 810 households were enrolled in the health care utilization survey and multipliers were derived based on responses to questions about health care seeking in the event of febrile illness. Of patients enrolled in fever surveillance over a 1 year period and residing in the 2 districts, 42 (7.14%) of 588 met the case definition for confirmed or probable leptospirosis. After applying multipliers to account for hospital selection, test sensitivity, and study enrollment, we estimated the overall incidence of leptospirosis ranges from 75-102 cases per 100,000 persons annually.Conclusions/significanceWe calculated a high incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania, where leptospirosis incidence was previously unknown. Multiplier methods, such as used in this study, may be a feasible method of improving availability of incidence estimates for neglected diseases, such as leptospirosis, in resource constrained settings.
Project description:The epidemiology of human malaria differs considerably between and within geographic regions due, in part, to variability in mosquito species behaviours. Recently, the WHO emphasised stratifying interventions using local surveillance data to reduce malaria. The usefulness of vector surveillance is entirely dependent on the biases inherent in the sampling methods deployed to monitor mosquito populations. To understand and interpret mosquito surveillance data, the frequency of use of malaria vector collection methods was analysed from a georeferenced vector dataset (> 10,000 data records), extracted from 875 manuscripts across Africa, the Americas and the Asia-Pacific region. Commonly deployed mosquito collection methods tend to target anticipated vector behaviours in a region to maximise sample size (and by default, ignoring other behaviours). Mosquito collection methods targeting both host-seeking and resting behaviours were seldomly deployed concurrently at the same site. A balanced sampling design using multiple methods would improve the understanding of the range of vector behaviours, leading to improved surveillance and more effective vector control.
Project description:ObjectiveThe Global Dietary Database (GDD) expanded its previous methods to harmonise and publicly disseminate individual-level dietary data from nutrition surveys worldwide.DesignAnalysis of cross-sectional data.SettingGlobal.ParticipantsGeneral population.MethodsComprehensive methods to streamline the harmonisation of primary, individual-level 24-h recall and food record data worldwide were developed. To standardise the varying food descriptions, FoodEx2 was used, a highly detailed food classification and description system developed and adapted for international use by European Food Safety Authority (EFSA). Standardised processes were developed to: identify eligible surveys; contact data owners; screen surveys for inclusion; harmonise data structure, variable definition and unit and food characterisation; perform data checks and publicly disseminate the harmonised datasets. The GDD joined forces with FAO and EFSA, given the shared goal of harmonising individual-level dietary data worldwide.ResultsOf 1500 dietary surveys identified, 600 met the eligibility criteria, and 156 were prioritised and contacted; fifty-five surveys were included for harmonisation and, ultimately, fifty two were harmonised. The included surveys were primarily nationally representative (59 %); included high- (39 %), upper-middle (21 %), lower-middle (27 %) and low- (13 %) income countries; usually collected multiple recalls/ records (64 %) and largely captured both sexes, all ages and both rural and urban areas. Surveys from low- and lower-middle v. high- and upper-middle income countries reported fewer nutrients (median 17 v. 30) and rarely included nutrients relevant to diet-related chronic diseases, such as n-3 fatty acids and Na.ConclusionsDiverse 24-h recalls/records can be harmonised to provide highly granular, standardised data, supporting nutrition programming, research and capacity development worldwide.
Project description:The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with an R2 value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses.
Project description:ObjectivesCurrently, there is no comprehensive picture of the global surveillance landscape. This survey examines the current state of surveillance systems, levels of integration, barriers and opportunities for the integration of surveillance systems at the country level, and the role of national public health institutes (NPHIs).Study designThis was a cross-sectional survey of NPHIs.MethodsA web-based survey questionnaire was disseminated to 110 NPHIs in 95 countries between July and August 2022. Data were descriptively analysed, stratified by World Health Organization region, World Bank Income Group, and self-reported Integrated Disease Surveillance (IDS) maturity status.ResultsSixty-five NPHIs responded. Systems exist to monitor notifiable diseases and vaccination coverage, but less so for private, pharmaceutical, and food safety sectors. While Ministries of Health usually lead surveillance, in many countries, NPHIs are also involved. Most countries report having partially developed IDS. Surveillance data are frequently inaccessible to the lead public health agency and seldomly integrated into a national public health surveillance system. Common challenges to establishing IDS include information technology system issues, financial constraints, data sharing and ownership limitations, workforce capacity gaps, and data availability.ConclusionsPublic health surveillance systems across the globe, although built on similar principles, are at different levels of maturity but face similar developmental challenges. Leadership, ownership and governance, supporting legal mandates and regulations, as well as adherence to mandates, and enforcement of regulations are critical components of effective surveillance. In many countries, NPHIs play a significant role in integrated disease surveillance.
Project description:ObjectivesShigella sonnei is a globally important diarrhoeal pathogen tracked through the surveillance network PulseNet Latin America and Caribbean (PNLA&C), which participates in PulseNet International. PNLA&C laboratories use common molecular techniques to track pathogens causing foodborne illness. We aimed to demonstrate the possibility and advantages of transitioning to whole genome sequencing (WGS) for surveillance within existing networks across a continent where S. sonnei is endemic.MethodsWe applied WGS to representative archive isolates of S. sonnei (n = 323) from laboratories in nine PNLA&C countries to generate a regional phylogenomic reference for S. sonnei and put this in the global context. We used this reference to contextualise 16 S. sonnei from three Argentinian outbreaks, using locally generated sequence data. Assembled genome sequences were used to predict antimicrobial resistance (AMR) phenotypes and identify AMR determinants.ResultsS. sonnei isolates clustered in five Latin American sublineages in the global phylogeny, with many (46%, 149 of 323) belonging to previously undescribed sublineages. Predicted multidrug resistance was common (77%, 249 of 323), and clinically relevant differences in AMR were found among sublineages. The regional overview showed that Argentinian outbreak isolates belonged to distinct sublineages and had different epidemiologic origins.ConclusionsLatin America contains novel genetic diversity of S. sonnei that is relevant on a global scale and commonly exhibits multidrug resistance. Retrospective passive surveillance with WGS has utility for informing treatment, identifying regionally epidemic sublineages and providing a framework for interpretation of prospective, locally sequenced outbreaks.