Sex-Specific Association of Ambient Temperature With Urine Biomarkers in Southwest Coastal Bangladesh.

Introduction: Men are vulnerable to ambient heat-related kidney disease burden; however, limited evidence exists on how vulnerable women are when exposed to high ambient heat. We evaluated the sex-specific association between ambient temperature and urine electrolytes, and 24-hour urine total protein, and volume. Methods: We pooled a longitudinal 5624 person-visits data of 1175 participants' concentration and 24-hour excretion of urine electrolytes and other biomarkers (24-hour urine total protein and volume) from southwest coastal Bangladesh (Khulna, Satkhira, and Mongla districts) during November 2016 to April 2017. We then spatiotemporally linked ambient temperature data from local weather stations to participants' health outcomes. For evaluating the relationships between average ambient temperature and urine electrolytes and other biomarkers, we plotted confounder-adjusted restricted cubic spline (RCS) plots using participant-level, household-level, and community-level random intercepts. We then used piece-wise linear mixed-effects models for different ambient temperature segments determined by inflection points in RCS plots and reported the maximum likelihood estimates and cluster robust standard errors. By applying interaction terms for sex and ambient temperature, we determined the overall significance using the Wald test. Bonferroni correction was used for multiple comparisons. Results: The RCS plots demonstrated nonlinear associations between ambient heat and urine biomarkers for males and females. Piecewise linear mixed-effects models suggested that sex did not modify the relationship of ambient temperature with any of the urine parameters after Bonferroni correction (P < 0.004). Conclusion: Our findings suggest that women are as susceptible to the effects of high ambient temperature exposure as men.

Analysis of environmental factors influencing endemic cholera risks in sub-Saharan Africa.

The recurring cholera outbreaks in sub-Saharan Africa are of growing concern, especially considering the potential acceleration in the global trend of larger and more lethal cholera outbreaks due to the impacts of climate change. However, there is a scarcity of evidence-based research addressing the environmental and infrastructure factors that sustain cholera recurrence in Africa. This study adopts a statistical approach to investigate over two decades of endemic cholera outbreaks and their relationship with five environmental factors: water provision, sanitation provision, raising temperatures, increased rainfall and GDP. The analysis covers thirteen of the forty-two countries in the mainland sub-Saharan region, collectively representing one-third of the region's territory and half of its population. This breadth enables the findings to be generalised at a regional level. Results from all analyses consistently associate water provision with cholera reduction. The stratified model links increased water provision with a reduction in cholera risk that ranged from 4.2 % to 84.1 % among eight countries (out of 13 countries) as well as a reduction of such risk that ranged from 9.8 % to 68.9 % when there is increased sanitation provision, which was observed in nine countries (out of 13). These results indicate that the population's limited access to water and sanitation, as well as the rise in temperatures, are critical infrastructure and environmental factors contributing to endemic cholera and the heightened risk of outbreaks across the sub-Saharan region. Therefore, these are key areas for targeted interventions and cross-border collaboration to enhance resilience to outbreaks and lead to the end of endemic cholera in the region. However, it is important to interpret the results of this study with caution; hence, further investigation is recommended to conduct a more detailed analysis of the impact of infrastructure and environmental factors on reducing cholera risk.

Positive and negative emotions during the COVID-19 pandemic: A longitudinal survey study of the UK population.

The COVID-19 pandemic has had a profound impact on society; it changed the way we work, learn, socialise, and move throughout the world. In the United Kingdom, policies such as business closures, travel restrictions, and social distance mandates were implemented to slow the spread of COVID-19 and implemented and relaxed intermittently throughout the response period. While negative emotions and feelings such as distress and anxiety during this time of crisis were to be expected, we also see the signs of human resilience, including positive feelings like determination, pride, and strength. A longitudinal study using online survey tools was conducted to assess people's changing moods during the pandemic in the UK. The Positive and Negative Affect Schedule (PANAS) was used to measure self-reported feelings and emotions throughout six periods (phases) of the study from March 2020 to July 2021. A total of 4,222 respondents participated in the survey, while a sub-group participated in each of the six study phases (n = 167). The results were analysed using a cross-sectional study design for the full group across each study phase, while prospective cohort analysis was used to assess the subset of participants who voluntarily answered the survey in each of the six study phases (n = 167). Gender, age and employment status were found to be most significant to PANAS score, with older people, retirees, and women generally reporting more positive moods, while young people and unemployed people generally reported lower positive scores and higher negative scores, indicating more negative emotions. Additionally, it was found that people generally reported higher positive feelings in the summer of 2021, which may be related to the relaxation of COVID-19-related policies in the UK as well as the introduction of vaccines for the general population. This study is an important investigation into what allows for positivity during a crisis and gives insights into periods or groups that may be vulnerable to increased negative states of emotions and feelings.

Gamified antimicrobial decision support app (GADSA) changes antibiotics prescription behaviour in surgeons in Nigeria: a hospital-based pilot study.

AIMS: Surgical Antibiotic Prophylaxis (SAP) in Nigeria is often not evidence based. The aim of this study is to test if the GADSA application can change prescription behaviour of surgeons in Nigeria. In addition, the study aims to identify AMS strategies and policies for the future. METHODS: The GADSA gamified decision support app uses WHO and Sanford prescribing guidelines to deliver real-time persuasive technology feedback to surgeons through an interactive mentor. The app can advise on whether clinician's decisions align with SAP recommendations and provides the opportunity for clinicians to make adjustments. Twenty surgeons actively participated in a 6-month pilot study in three hospitals in Nigeria. The surgeons determined the risk of infection of a surgical procedure, and the need, type and duration of SAP. The study used a longitudinal approach to test whether the GADSA app significantly changed prescribing behaviour of participating surgeons by analysing the reported prescription decisions within the app. RESULTS: 321 SAP prescriptions were recorded. Concerning the surgical risk decision, 12% of surgeons changed their decision to be in line with guidelines after app feedback (p < 0.001) and 10% of surgeons changed their decision about the need for SAP (p = 0.0035) to align with guidelines. The change in decision making for SAP use in terms of "type" and "duration" to align with guidelines was similar with 6% and 5% respectively (both p-values < 0.001). CONCLUSION: This study suggests that the GADSA app, with its game based and feedback feature, could significantly change prescribing behaviour at the point of care in an African setting, which could help tackle the global challenge of antibiotic resistance.

Call detail record aggregation methodology impacts infectious disease models informed by human mobility.

This paper demonstrates how two different methods used to calculate population-level mobility from Call Detail Records (CDR) produce varying predictions of the spread of epidemics informed by these data. Our findings are based on one CDR dataset describing inter-district movement in Ghana in 2021, produced using two different aggregation methodologies. One methodology, "all pairs," is designed to retain long distance network connections while the other, "sequential" methodology is designed to accurately reflect the volume of travel between locations. We show how the choice of methodology feeds through models of human mobility to the predictions of a metapopulation SEIR model of disease transmission. We also show that this impact varies depending on the location of pathogen introduction and the transmissibility of infections. For central locations or highly transmissible diseases, we do not observe significant differences between aggregation methodologies on the predicted spread of disease. For less transmissible diseases or those introduced into remote locations, we find that the choice of aggregation methodology influences the speed of spatial spread as well as the size of the peak number of infections in individual districts. Our findings can help researchers and users of epidemiological models to understand how methodological choices at the level of model inputs may influence the results of models of infectious disease transmission, as well as the circumstances in which these choices do not alter model predictions.

Analyses of reported severe adverse events after immunization with SARS-CoV-2 vaccines in the United States: One year on.

Objective: To analyze rates of reported severe adverse events after immunization (sAEFI) attributed to SARS-CoV-2 vaccines in the United States (US) using safety surveillance data. Methods: Observational study of sAEFI reported to the vaccine adverse events reporting system (VAERS) between December 13, 2020, to December 13, 2021, and attributed to SARS-CoV-2 vaccination programs across all US states and territories. All sAEFI in conjunction with mRNA (BNT-162b2 or mRNA-1273) or adenovector (Ad26.COV2.S) vaccines were included. The 28-day crude cumulative rates for reported emergency department (ED) visits and sAEFI viz. hospitalizations, life-threatening events and deaths following SARS-CoV-2 vaccination were calculated. Incidence rate ratios (IRRs) of reported sAEFI were compared between mRNA and adenovector vaccines using generalized Poisson regression models. Results: During the study period, 485 million SARS-CoV-2 vaccines doses were administered nationwide, and 88,626 sAEFI reported in VAERS. The 28-day crude cumulative reporting rates per 100,000 doses were 14.97 (95% confidence interval, 14.86-18.38) for ED visits, 5.32 (5.26-5.39) for hospitalizations, 1.72 (1.68-1.76) for life-threatening events, and 1.08 (1.05-1.11) for deaths. Females had two-fold rates for any reported AEFI compared to males, but lower adjusted IRRs for sAEFI. Cumulative rates per dose for reported sAEFI attributed to adenovector vaccine were 2-3-fold higher, and adjusted IRRs 1.5-fold higher than mRNA vaccines. Conclusions: Overall cumulative rates for reported sAEFI following SARS-CoV-2 vaccination in the US over 1 year were very low; single-dose adenovector vaccine had 1.5-fold higher adjusted rates for reported sAEFI, which may however equate with multiple-doses mRNA vaccine regimens. These data indicate absence of high risks of sAEFI following SARS-CoV-2 vaccines and support safety equipoise between mRNA and adenovector vaccines. Public health messaging of these data is critical to overcome heuristic biases. Furthermore, these data may support ongoing adenovector vaccine use, especially in low- and middle-income countries due to affordability, logistical and cold chain challenges.

Epidemiology, diagnostics and factors associated with mortality during a cholera epidemic in Nigeria, October 2020-October 2021: a retrospective analysis of national surveillance data.

OBJECTIVES: Nigeria reported an upsurge in cholera cases in October 2020, which then transitioned into a large, disseminated epidemic for most of 2021. This study aimed to describe the epidemiology, diagnostic performance of rapid diagnostic test (RDT) kits and the factors associated with mortality during the epidemic. DESIGN: A retrospective analysis of national surveillance data. SETTING: 33 of 37 states (including the Federal Capital Territory) in Nigeria. PARTICIPANTS: Persons who met cholera case definition (a person of any age with acute watery diarrhoea, with or without vomiting) between October 2020 and October 2021 within the Nigeria Centre for Disease Control surveillance data. OUTCOME MEASURES: Attack rate (AR; per 100 000 persons), case fatality rate (CFR; %) and accuracy of RDT performance compared with culture using area under the receiver operating characteristic curve (AUROC). Additionally, individual factors associated with cholera deaths and hospitalisation were presented as adjusted OR with 95% CIs. RESULTS: Overall, 93 598 cholera cases and 3298 deaths (CFR: 3.5%) were reported across 33 of 37 states in Nigeria within the study period. The proportions of cholera cases were higher in men aged 5-14 years and women aged 25-44 years. The overall AR was 46.5 per 100 000 persons. The North-West region recorded the highest AR with 102 per 100 000. Older age, male gender, residency in the North-Central region and severe dehydration significantly increased the odds of cholera deaths. The cholera RDT had excellent diagnostic accuracy (AUROC=0.91; 95% CI 0.87 to 0.96). CONCLUSIONS: Cholera remains a serious public health threat in Nigeria with a high mortality rate. Thus, we recommend making RDT kits more widely accessible for improved surveillance and prompt case management across the country.

To Zoom or not to Zoom: A longitudinal study of UK population's activities during the COVID-19 pandemic.

This longitudinal study determines the frequency and way of people doing activities from Spring 2020 to Summer 2021 during different phases of the COVID-19 pandemic in the UK. Six online surveys were carried out between April 2020 and July 2021. 4,992 participants were engaged in the cross-sectional study and 203 participants who provided repeat responses were included in the subset sample of prospective cohort analysis. Primary outcomes measured were the frequency and the mode of doing the activities (online or in-person) across sixteen selected activity groups, as defined by the UK National Time Use Survey. The results show that cultural activities, spending time with others, and travelling, were the activities with the largest proportions of frequency and mode changes. The most significant changes occurred from March to June 2020, a period that included the first lockdown. Survey results from this period show a significant decrease among most of the sixteen measured activities. From March to October 2020, a period which spans the first lockdown and its subsequent ease of restrictions, showed the most significant shift from accessing activities in-person to online. Despite 'Freedom Day', the July 19th 2021 date in which all restrictions were abolished, it was found that people do cultural activities and group activities at a significantly lower frequency than before the pandemic. In addition, despite a lack of restrictions after this date, more than half of participants access many activities, such as spending time with others, shopping, work and studying, online or hybrid. This study provides an invaluable insight into understanding how people in the UK changed their lifestyle, including what activities they do, and how they accessed those activities in light of the COVID-19 pandemic and related public health policy implemented to address the pandemic. These results may serve as unique evidence for policymakers.

Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning: A Systematic Review.

Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed by a combination of climatic, environmental, and human mobility factors. Arboviruses prediction models can be a support tool for decision-making by public health agents. In this study, we propose a systematic literature review to identify arboviruses prediction models, as well as models for their transmitter vector dynamics. To carry out this review, we searched reputable scientific bases such as IEE Xplore, PubMed, Science Direct, Springer Link, and Scopus. We search for studies published between the years 2015 and 2020, using a search string. A total of 429 articles were returned, however, after filtering by exclusion and inclusion criteria, 139 were included. Through this systematic review, it was possible to identify the challenges present in the construction of arboviruses prediction models, as well as the existing gap in the construction of spatiotemporal models.

Exploring barriers to guideline implementation for prescription of surgical antibiotic prophylaxis in Nigeria.

Background: In Nigeria, the prescription of surgical antibiotic prophylaxis for prevention of surgical site infection tends to be driven by local policy rather than by published guidelines (e.g. WHO and Sanford). Objectives: To triangulate three datasets and understand key barriers to implementation using a behavioural science framework. Methods: Surgeons (N = 94) from three teaching hospitals in Nigeria participated in an online survey and in focus group discussions about barriers to implementation. The theoretical domains framework (TDF) was used to structure question items and interview schedules. A subgroup (N = 20) piloted a gamified decision support app over the course of 6 months and reported barriers at the point of care. Results: Knowledge of guidelines and intention to implement them in practice was high. Key barriers to implementation were related to environmental context and resources and concern over potential consequences of implementing recommendations within the Nigerian context applicable for similar settings in low-to-middle-income countries. Conclusions: The environmental context and limited resource setting of Nigerian hospitals currently presents a significant barrier to implementation of WHO and Sanford guidelines. Research and data collected from the local context must directly inform the writing of future international guidelines to increase rates of implementation.

COVID-19 mortality rate and its associated factors during the first and second waves in Nigeria.

COVID-19 mortality rate has not been formally assessed in Nigeria. Thus, we aimed to address this gap and identify associated mortality risk factors during the first and second waves in Nigeria. This was a retrospective analysis of national surveillance data from all 37 States in Nigeria between February 27, 2020, and April 3, 2021. The outcome variable was mortality amongst persons who tested positive for SARS-CoV-2 by Reverse-Transcriptase Polymerase Chain Reaction. Incidence rates of COVID-19 mortality was calculated by dividing the number of deaths by total person-time (in days) contributed by the entire study population and presented per 100,000 person-days with 95% Confidence Intervals (95% CI). Adjusted negative binomial regression was used to identify factors associated with COVID-19 mortality. Findings are presented as adjusted Incidence Rate Ratios (aIRR) with 95% CI. The first wave included 65,790 COVID-19 patients, of whom 994 (1∙51%) died; the second wave included 91,089 patients, of whom 513 (0∙56%) died. The incidence rate of COVID-19 mortality was higher in the first wave [54∙25 (95% CI: 50∙98-57∙73)] than in the second wave [19∙19 (17∙60-20∙93)]. Factors independently associated with increased risk of COVID-19 mortality in both waves were: age ≥45 years, male gender [first wave aIRR 1∙65 (1∙35-2∙02) and second wave 1∙52 (1∙11-2∙06)], being symptomatic [aIRR 3∙17 (2∙59-3∙89) and 3∙04 (2∙20-4∙21)], and being hospitalised [aIRR 4∙19 (3∙26-5∙39) and 7∙84 (4∙90-12∙54)]. Relative to South-West, residency in the South-South and North-West was associated with an increased risk of COVID-19 mortality in both waves. In conclusion, the rate of COVID-19 mortality in Nigeria was higher in the first wave than in the second wave, suggesting an improvement in public health response and clinical care in the second wave. However, this needs to be interpreted with caution given the inherent limitations of the country's surveillance system during the study.

MEWAR: Development of a Cross-Platform Mobile Application and Web Dashboard System for Real-Time Mosquito Surveillance in Northeast Brazil.

Mosquito surveillance is a crucial process for understanding the population dynamics of mosquitoes, as well as implementing interventional programs for controlling and preventing the spread of mosquito-borne diseases. Environmental surveillance agents who performing routine entomological surveys at properties in areas where mosquito-borne diseases are endemic play a critical role in vector surveillance by searching and destroying mosquito hotspots as well as collate information on locations with increased infestation. Currently, the process of recording information on paper-based forms is time-consuming and painstaking due to manual effort. The introduction of mobile surveillance applications will therefore improve the process of data collection, timely reporting, and field worker performance. Digital-based surveillance is critical in reporting real-time data; indeed, the real-time capture of data with phones could be used for predictive analytical models to predict mosquito population dynamics, enabling early warning detection of hotspots and thus alerting fieldworker agents into immediate action. This paper describes the development of a cross-platform digital system for improving mosquito surveillance in Brazil. It comprises of two components: a dashboard for managers and a mobile application for health agents. The former enables managers to assign properties to health workers who then survey them for mosquitoes and to monitor the progress of inspection visits in real-time. The latter, which is primarily designed as a data collection tool, enables the environmental surveillance agents to act on their assigned tasks of recording the details of the properties at inspections by filling out digital forms built into the mobile application, as well as details relating to mosquito infestation. The system presented in this paper was co-developed with significant input with environmental agents in two Brazilian cities where it is currently being piloted.

A review exploring the overarching burden of Zika virus with emphasis on epidemiological case studies from Brazil.

This paper explores the main factors for mosquito-borne transmission of the Zika virus by focusing on environmental, anthropogenic, and social risks. A literature review was conducted bringing together related information from this genre of research from peer-reviewed publications. It was observed that environmental conditions, especially precipitation, humidity, and temperature, played a role in the transmission. Furthermore, anthropogenic factors including sanitation, urbanization, and environmental pollution promote the transmission by affecting the mosquito density. In addition, socioeconomic factors such as poverty as well as social inequality and low-quality housing have also an impact since these are social factors that limit access to certain facilities or infrastructure which, in turn, promote transmission when absent (e.g., piped water and screened windows). Finally, the paper presents short-, mid-, and long-term preventative solutions together with future perspectives. This is the first review exploring the effects of anthropogenic aspects on Zika transmission with a special emphasis in Brazil.

Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting.

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post-the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics.

COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19.

Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil. Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented. Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, Maranhão, Piauí, Rio Grande do Norte, Amapá, Rondônia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for Espírito Santo, Minas Gerais, Paraná, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%. Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America.

What are the drivers of recurrent cholera transmission in Nigeria? Evidence from a scoping review.

BACKGROUND: The 2018 cholera outbreak in Nigeria affected over half of the states in the country, and was characterised by high attack and case fatality rates. The country continues to record cholera cases and related deaths to date. However, there is a dearth of evidence on context-specific drivers and their operational mechanisms in mediating recurrent cholera transmission in Nigeria. This study therefore aimed to fill this important research gap, with a view to informing the design and implementation of appropriate preventive and control measures. METHODS: Four bibliographic literature sources (CINAHL (Plus with full text), Web of Science, Google Scholar and PubMed), and one journal (African Journals Online) were searched to retrieve documents relating to cholera transmission in Nigeria. Titles and abstracts of the identified documents were screened according to a predefined study protocol. Data extraction and bibliometric analysis of all eligible documents were conducted, which was followed by thematic and systematic analyses. RESULTS: Forty-five documents met the inclusion criteria and were included in the final analysis. The majority of the documents were peer-reviewed journal articles (89%) and conducted predominantly in the context of cholera epidemics (64%). The narrative analysis indicates that social, biological, environmental and climatic, health systems, and a combination of two or more factors appear to drive cholera transmission in Nigeria. Regarding operational dynamics, a substantial number of the identified drivers appear to be functionally interdependent of each other. CONCLUSION: The drivers of recurring cholera transmission in Nigeria are diverse but functionally interdependent; thus, underlining the importance of adopting a multi-sectoral approach for cholera prevention and control.

Identifying and quantifying the factors associated with cholera-related death during the 2018 outbreak in Nigeria.

INTRODUCTION: cholera outbreaks in Nigeria are often associated with high case fatality rates; however, there is a dearth of evidence on context-specific factors associated with the trend. This study therefore aimed to identify and quantify the factors associated with cholera-related deaths in Nigeria. METHODS: using a cross-sectional design, we analysed surveillance data from all the States that reported cholera cases during the 2018 outbreak, and defined cholera-related death as death of an individual classified as having cholera according to the Nigeria Centre for Disease Control case definition. Factors associated with cholera-related death were assessed using multivariable logistic regression and findings presented as adjusted odds ratios (ORs) with 95% Confidence Intervals (95% CIs). RESULTS: between January 1 and November 19, 2018, 41,394 cholera cases were reported across 20 States, including 815 cholera-related deaths. In the adjusted multivariable model, older age, male gender, living in peri-urban areas or in flooded states, infection during the rainy season, and delay in seeking health care by >2 days were positively associated with cholera-related death; whereas living in urban areas, hospitalisation in the course of illness, and presentation to a secondary hospital were negatively associated with cholera-related death. CONCLUSION: cholera-related deaths during the 2018 outbreak in Nigeria appeared to be driven by multiple factors, which further reemphasises the importance of adopting a multisectoral approach to the design and implementation of context-specific interventions in Nigeria.

Descriptive epidemiology of cholera outbreak in Nigeria, January-November, 2018: implications for the global roadmap strategy.

BACKGROUND: The cholera outbreak in 2018 in Nigeria reaffirms its public health threat to the country. Evidence on the current epidemiology of cholera required for the design and implementation of appropriate interventions towards attaining the global roadmap strategic goals for cholera elimination however seems lacking. Thus, this study aimed at addressing this gap by describing the epidemiology of the 2018 cholera outbreak in Nigeria. METHODS: This was a retrospective analysis of surveillance data collected between January 1st and November 19th, 2018. A cholera case was defined as an individual aged 2 years or older presenting with acute watery diarrhoea and severe dehydration or dying from acute watery diarrhoea. Descriptive analyses were performed and presented with respect to person, time and place using appropriate statistics. RESULTS: There were 43,996 cholera cases and 836 cholera deaths across 20 states in Nigeria during the outbreak period, with an attack rate (AR) of 127.43/100,000 population and a case fatality rate (CFR) of 1.90%. Individuals aged 15 years or older (47.76%) were the most affected age group, but the proportion of affected males and females was about the same (49.00 and 51.00% respectively). The outbreak was characterised by four distinct epidemic waves, with higher number of deaths recorded in the third and fourth waves. States from the north-west and north-east regions of the country recorded the highest ARs while those from the north-central recorded the highest CFRs. CONCLUSION: The severity and wide-geographical distribution of cholera cases and deaths during the 2018 outbreak are indicative of an elevated burden, which was more notable in the northern region of the country. Overall, the findings reaffirm the strategic role of a multi-sectoral approach in the design and implementation of public health interventions aimed at preventing and controlling cholera in Nigeria.

Health status of returning refugees, internally displaced persons, and the host community in a post-conflict district in northern Sri Lanka: a cross-sectional survey.

BACKGROUND: Although the adverse impacts of conflict-driven displacement on health are well-documented, less is known about how health status and associated risk factors differ according to displacement experience. This study quantifies health status and quality of life among returning refugees, internally displaced persons, and the host community in a post-conflict district in Northern Sri Lanka, and explores associated risk factors. METHODS: We analysed data collected through a household survey (n = 570) in Vavuniya district, Sri Lanka. The effect of displacement status and other risk factors on perceived quality of life as estimated from the 36-item Short Form Questionnaire, mental health status from 9-item Patient Health Questionnaire, and self-reported chronic disease status were examined using univariable analyses and multivariable regressions. RESULTS: We found strong evidence that perceived quality of life was significantly lower for internally displaced persons than for the host community and returning refugees, after adjusting for covariates. Both mental health status and chronic disease status did not vary remarkably among the groups, suggesting that other risk factors might be more important determinants of these outcomes. CONCLUSIONS: Our study provides important insights into the overall health and well-being of the different displaced sub-populations in a post-conflict setting. Findings reinforce existing evidence on the relationship between displacement and health but also highlight gaps in research on the long-term health effects of prolonged displacement. Understanding the heterogeneity of conflict-affected populations has important implications for effective and equitable humanitarian service delivery in a post-conflict setting.

Linkage of national soil quality measurements to primary care medical records in England and Wales: a new resource for investigating environmental impacts on human health.

BACKGROUND: Long-term, low-level exposure to toxic elements in soil may be harmful to human health but large longitudinal cohort studies with sufficient follow-up time to study these effects are cost-prohibitive and impractical. Linkage of routinely collected medical outcome data to systematic surveys of soil quality may offer a viable alternative. METHODS: We used the Geochemical Baseline Survey of the Environment (G-BASE), a systematic X-ray fluorescence survey of soil inorganic chemistry throughout England and Wales to obtain estimates of the concentrations of 15 elements in the soil contained within each English and Welsh postcode area. We linked these data to the residential postcodes of individuals enrolled in The Health Improvement Network (THIN), a large database of UK primary care medical records, to provide estimates of exposure. Observed exposure levels among the THIN population were compared with expectations based on UK population estimates to assess representativeness. RESULTS: Three hundred seventy-seven of three hundred ninety-five English and Welsh THIN practices agreed to participate in the linkage, providing complete residential soil metal estimates for 6,243,363 individuals (92% of all current and former patients) with a mean period of prospective computerised medical data collection (follow-up) of 6.75 years. Overall agreement between the THIN population and expectations was excellent; however, the number of participating practices in the Yorkshire & Humber strategic health authority was low, leading to restricted ranges of measurements for some elements relative to the known variations in geochemical concentrations in this area. CONCLUSIONS: The linked database provides unprecedented population size and statistical power to study the effects of elements in soil on human health. With appropriate adjustment, results should be generalizable to and representative of the wider English and Welsh population.