Disease Surveillance Data Research Articles

Application of the screening method for estimating COVID-19 vaccine effectiveness using routine surveillance data: Germany's experience during the COVID-19 pandemic, July 2021 to March 2023.

The screening method represents a simple, quick, and practical tool for estimating vaccine effectiveness (VE) using routine disease surveillance and vaccine coverage data, even if these data cannot be linked. In Germany, where notification data, laboratory testing data, and vaccine coverage data cannot be linked due to strict data protection requirements, the screening method was used to assess COVID-19 VE continuously between July 2021 and March 2023. During this period, when Delta and Omicron variants circulated, VE estimates were produced in real-time for different age groups and clinical outcomes. Here we describe the country's overall positive experience using the screening method, including its strengths and limitations, and provide practical guidance regarding a few issues, such as case definition stringency, testing behaviour, and data stratification, that require careful consideration during data analysis and the interpretation of the results.

First malaria in pregnancy followed in Philippine real-world setting: proof-of-concept of probabilistic record linkage between disease surveillance and hospital administrative data

BackgroundAlthough the Philippines targets malaria elimination by 2030, it remains to be a disease that causes considerable morbidity in provinces that report malaria. Pregnant women residing in endemic areas are a vulnerable population, because in addition to the risk of developing severe malaria, their pregnancy is not followed through, and the outcome of their pregnancy is unknown. This study determined the utility of real-world data integrated with disease surveillance data set as real-world evidence of pregnancy and delivery outcomes in areas endemic for malaria in the Philippines.MethodsFor the period of 2015 to 2019, electronic data sets of malaria surveillance data and Ospital ng Palawan hospital admission log of pregnant women residing in the four selected barangays of Rizal, Palawan were merged using probabilistic linkage. The source data for record linkage were first and last names, birth date, and address as the mutual variable. The data used for characteristics of the pregnant women from the hospital data set were admission date, discharge date, admitting and final diagnosis and body weight on admission. From the malaria surveillance data these were date of consultation, and malaria parasite species. The Levenshtein distance formula was used for a fuzzy string-matching algorithm. Chi-square test, and Mann–Whitney U test were used to compare the means of the two data sets.ResultsThe prevalence of pregnant women admitted to the tertiary referral hospital, Ospital ng Palawan, was estimated to be 8.34/100 overall, and 11.64/100 from the four study barangays; that of malaria during pregnancy patients was 3.45/100 and 2.64/100, respectively. There was only one true-positive matched case from 238 women from the hospital and 54 women from the surveillance data sets. The overall Levenshstein score was 97.7; for non-matched cases, the mean overall score was 36.6 (35.6–37.7). The matched case was a minor who was hospitalized for severe malaria. The outcome of her pregnancy was detected from neither data set but from village-based records.ConclusionsThis proof-of-concept study demonstrated that probabilistic record linkage could match real-world data in the Philippines with further validation required. The study underscored the need for more integrated and comprehensive database to monitor disease intervention impact on pregnancy and its outcome in the Philippines.

Forecasting seasonal influenza activity in Canada-Comparing seasonal Auto-Regressive integrated moving average and artificial neural network approaches for public health preparedness.

Public health preparedness is based on timely and accurate information. Time series forecasting using disease surveillance data is an important aspect of preparedness. This study compared two approaches of time series forecasting: seasonal auto-regressive integrated moving average (SARIMA) modelling and the artificial neural network (ANN) algorithm. The goal was to model weekly seasonal influenza activity in Canada using SARIMA and compares its predictive accuracy, based on root mean square prediction error (RMSE) and mean absolute prediction error (MAE), to that of an ANN. An initial SARIMA model was fit using automated model selection by minimizing the Akaike information criterion (AIC). Further inspection of the autocorrelation function and partial autocorrelation function led to 'manual' model improvements. ANNs were trained iteratively, using an automated process to minimize the RMSE and MAE. A total of 378, 462 cases of influenza was reported in Canada from the 2010-2011 influenza season to the end of the 2019-2020 influenza season, with an average yearly incidence risk of 20.02 per 100,000 population. Automated SARIMA modelling was the better method in terms of forecasting accuracy (per RMSE and MAE). However, the ANN correctly predicted the peak week of disease incidence while the other models did not. Both the ANN and SARIMA models have shown to be capable tools in forecasting seasonal influenza activity in Canada. It was shown that applying both in tandem is beneficial, SARIMA better forecasted overall incidence while ANN correctly predicted the peak week.

Epidemiologic changes of a longitudinal surveillance study spanning 51 years of scrub typhus in mainland China

Scrub typhus may be one of the world’s most prevalent, neglected and serious, but easily treatable, febrile diseases. It has become a significant potential threat to public health in China. In this study we used national disease surveillance data to analyze the incidence and spatial–temporal distribution of scrub typhus in mainland China during 1952–1989 and 2006–2018. Descriptive epidemiological methods and spatial–temporal epidemiological methods were used to investigate the epidemiological trends and identify high-risk regions of scrub typhus infection. Over the 51-year period, a total of 182,991 cases and 186 deaths were notified. The average annual incidence was 0.13 cases/100,000 population during 1952–1989. The incidence increased sharply from 0.09/100,000 population in 2006 to 1.93/100,000 population in 2018 and then exponentially increased after 2006. The incidence was significantly higher in females than males (χ2 = 426.32, P < 0.001). Farmers had a higher incidence of scrub typhus than non-farmers (χ2 = 684.58, P < 0.001). The majority of cases each year were reported between July and November with peak incidence occurring during October each year. The trend surface analysis showed that the incidence of scrub typhus increased gradually from north to south, and from east and west to the central area. The spatial autocorrelation analysis showed that a spatial positive correlation existed in the prevalence of scrub typhus on a national scale, which had the characteristic of aggregated distribution (I = 0.533, P < 0.05). LISA analysis showed hotspots (High–High) were primarily located in the southern and southwestern provinces of China with the geographical area expanding annually. These findings provide scientific evidence for the surveillance and control of scrub typhus which may contribute to targeted strategies and measures for the government.

Knowledge, perceptions, and practices around zoonotic diseases among actors in the livestock trade in the Lake Victoria crescent ecosystem in East Africa.

Zoonotic diseases such as anthrax, rabies, brucellosis, and Rift Valley fever pose a direct threat to health and undercut livelihoods in the communities in which they occur. A combination of anthropogenic and animal activities like migration and interaction with wildlife and their respective parasites and vectors drives the emergence and re-emergence of zoonotic diseases. Consequently, One Health interdisciplinary approaches that incorporate social scientists can provide key insights into complex local perceptions. The approach calls for collaboration between the human and animal health sectors, including the sharing of disease surveillance data necessary to alleviate disease impacts. Livestock traders interact closely with livestock, which puts them at elevated risk of infection and creates conditions by which they may spread zoonotic disease. It is thus essential to examine practices among actors involved in the livestock trade to understand the most appropriate ways to mitigate these risks. A qualitative study was conducted among the actors in the livestock trade in Busia County on their knowledge and perceptions of zoonotic diseases and practices that may contribute to the spread, control, and prevention of zoonotic disease transmission. A thematic analysis framework was used to categorize and synthesize data from in-depth interviews (IDIs), key informant interviews (KIIs), and structured observations. Whereas participants could list livestock diseases, they could not identify which ones were zoonoses, demonstrating insufficient knowledge of zoonosis. They identify sick animals by checking for dropped ears, excess mucus production, diarrhea, bloody urinal discharge, and general animal activity levels. To prevent the spread of these diseases, they wash their animals, isolate sick animals from the rest of the stock, and vaccinate their animals. They seek help from animal health professionals for sick animals as part of curative practices. This shows that they perceive the diseases as serious and that they need to be attended to by professionals. The results also show that they perceive animals from outside the region to be more vulnerable to diseases compared to those from within. The actors in the livestock trade engage in practices like skinning dead animals before burying them; to them, this is a normal practice. Some also consume dead carcasses. These increase the risk of zoonotic disease transmission. The actors involved in the livestock trade are critical in the prevention and elimination of zoonotic diseases; hence, they need to be involved when developing intervention programs and policies for animal health extension services. Training them as a continuum of animal health workers blends lay and professional knowledge, which, alongside their intense contact with large numbers of animals, becomes a critical disease surveillance tool. Increasing awareness of zoonoses by using multi-disciplinary teams with social scientists is urgently needed so that practices like skinning dead animals before disposing of them and consumption of dead carcasses can be minimized.

Water and war: The effect of functioning chlorinated water stations in reducing waterborne diseases during conflict in northwest Syria, 2017-2021.

Since 2011, Syria has been engulfed in a complex conflict marked by both targeted and indiscriminate attacks on civilians and civilian infrastructure. Water infrastructure has been continuously targeted, exacerbating problems with contamination of and access to clean adequate drinking water, and increasing the risk of waterborne diseases. We aimed to determine whether having access to more functional and chlorinated water stations is associated with a reduced risk of waterborne disease in northwest Syria. We examined the effect of functioning chlorinated water stations on the incidence of waterborne disease in 10 districts of Northwest Syria between January 1, 2017, and June 30, 2021, using weekly reported disease surveillance data and data from a water, sanitation, and hygiene (WASH) system evaluation program of the Assistance Coordination Unit (ACU). We ran eight negative binomial models to examine the association between functioning chlorinated water stations and the incidence of four of the five waterborne diseases: acute bloody diarrhea (ABD), acute other diarrhea (AOD), acute jaundice syndrome (AJS), and severe typhoid fever (STF). Dose-response models were used to investigate how the incidence of disease can theoretically be reduced as functioning and chlorinated water stations strategically increase. Compared to areas with lower quintiles of functioning and chlorinated water stations, the rates of the four waterborne diseases were lower in areas with higher quintiles of functioning and chlorinated water stations. Exposure to functioning water stations had a stronger association with lower rates of waterborne diseases than exposure to chlorinated water stations. Dose-response models demonstrate a potential for curbing the incidence of acute diarrhea and acute jaundice syndrome. The results of this study provide an understanding of the effects of water station functionality and chlorination in conflict settings. These findings support greater prioritization of WASH activities in countries experiencing violence against civilian infrastructure.

Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts.

Since 8th March 2020 up to the time of writing, we have been producing near real-time weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for all countries with evidence of sustained transmission, shared online. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. Here we present a retrospective evaluation of the forecasts produced between 8th March to 29th November 2020 for 81 countries. We evaluated the robustness of the forecasts produced in real-time using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3% and 45.6% of the observations lying in the 50% Credible Interval in 1-week and 4-week ahead forecasts respectively. The retrospective evaluation of our models shows that simple transmission models calibrated using routine disease surveillance data can reliably capture the epidemic trajectory in multiple countries. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures.

Fostering Governance and Information Partnerships for Chronic Disease Surveillance: The Multi-State EHR-Based Network for Disease Surveillance.

Electronic health records (EHRs) are an emerging chronic disease surveillance data source and facilitating this data sharing is complex. Using the experience of the Multi-State EHR-Based Network for Disease Surveillance (MENDS), this article describes implementation of a governance framework that aligns technical, statutory, and organizational requirements to facilitate EHR data sharing for chronic disease surveillance. MENDS governance was cocreated with data contributors and health departments representing Texas, New Orleans, Louisiana, Chicago, Washington, and Indiana through engagement from 2020 to 2022. MENDS convened a governance body, executed data-sharing agreements, and developed a master governance document to codify policies and procedures. The MENDS governance committee meets regularly to develop policies and procedures on data use and access, timeliness and quality, validation, representativeness, analytics, security, small cell suppression, software implementation and maintenance, and privacy. Resultant policies are codified in a master governance document. The MENDS governance approach resulted in a transparent governance framework that cultivates trust across the network. MENDS's experience highlights the time and resources needed by EHR-based public health surveillance networks to establish effective governance.

ANALISIS KESTABILAN MODEL SVIQR PADA PENYEBARAN PENYAKIT DIFTERI DENGAN PENGARUH VAKSINASI DAN KARANTINA

Diphtheria is an acute disease caused by bacteria (Corynebacterium Diphtheriae). This disease is transmitted through the air and droplets (very small drops of fluid) from infected individuals. Vaccination can be carried out as a preventive measure so as not to be infected with bacteria (Corynebacterium Diphtheriae) and quarantine is carried out as a healing process because this disease is one type of disease included in the hospital-based STP (Integrated Disease Surveillance) data source. This study aims to compile and analyze a model of the spread of diphtheria using the SVIQR model. This model contains five subpopulations, namely susceptible (S), infected (I), cured (R), quarantined (Q) and vaccinated (V). Then determine the numerical simulation by estimating the parameters. From the results of numerical simulations of the mathematical model of diphtheria transmission under the influence of vaccination and quarantine, it shows that by selecting the vaccination fade rate parameter, =0.3795491181&lt;1, which means that the disease-free equilibrium point is stable. The asymptotically stable endemic equilibrium point obtained is =1.207495030&gt;1. The smaller the value of the vaccination fading rate parameter ε, the more asymptotically stable the disease-free point means that the spread of disease or endemic disease can be prevented if the vaccine given does not fade easily.&#x0D; Keywords: Stability Analysis, Mathematical Models, Diphtheria, Quarantine, Vaccination.

Predicting the dengue cluster outbreak dynamics in Yogyakarta, Indonesia: a modelling study.

Human mobility and climate conditions are recognised key drivers of dengue transmission, but their combined and individual role in the local spatiotemporal clustering of dengue cases is not well understood. This study investigated the effects of human mobility and weather conditions on dengue risk in an urban area in Yogyakarta, Indonesia. We established a Bayesian spatiotemporal model for neighbourhood outbreak prediction and evaluated the performances of two different approaches for constructing an adjacency matrix: one based on geographical proximity and the other based on human mobility patterns. We used population, weather conditions, and past dengue cases as predictors using a flexible distributed lag approach. The human mobility data were estimated based on proxies from social media. Unseen data from February 2017 to January 2020 were used to estimate the one-month ahead prediction accuracy of the model. When human mobility proxies were included in the spatial covariance structure, the model fit improved in terms of the log score (from 1.748 to 1.561) and the mean absolute error (from 0.676 to 0.522) based on the validation data. Additionally, showed only few observations outside the credible interval of predictions (1.48%) and weather conditions were not found to contribute additionally to the clustering of cases at this scale. The study shows that it is possible to make highly accurate predictions of the within-city cluster dynamics of dengue using mobility proxies from social media combined with disease surveillance data. These insights are important for proactive and timely outbreak management of dengue. Swedish Research Council Formas, Umeå Centre for Global Health Research, Swedish Council for Working Life and Social Research, Swedish research council VINNOVA and Alexander von Humboldt Foundation (Germany).

BSL‐4 laboratories, combatting conspiracies, and using a culture‐centered approach to improve risk and crisis communication in a One Health framework

AbstractThe COVID‐19 pandemic continues to pose a global zoonotic disease threat, highlighting the importance of developing strategies to combat new viruses and variants stemming from climate change and animal populations. A multidisciplinary approach is needed to address dis/misinformation surrounding such research. Collaborations across disciplines aid in actual responses to public health emergency events as well, easing the transition to a new equilibrium and impacting planning for future events. Russian disinformation regarding the joint work of Americans and Ukrainians as part of the Biological Threat Reduction Program is evidence of the need to educate the public about the real risks and benefits of zoonotic disease research. As seen in the recently released National Biodefense Strategy, political leaders in the United States are becoming more explicit about embracing a One Health framework for biodefense and public health emergency preparedness. This has significant benefits in terms of policy making by helping to dispel dis/misinformation, build trust in disease surveillance data, and give frontline workers such as those in the agricultural sector a voice in the conversation with which to share their expertise. A communication complex perspective applied through a culture‐centered approach to a One Health model aims to improve risk and crisis communication. This unique strategy will help government leaders as well as those in relevant sectors to speak to the unique questions and concerns of a particular population. Among other things, this helps to avoid an ineffective “cookie‐cutter” approach messaging. In this manuscript, we argue that coconstructing a cultural understanding of human, animal, and environmental health practices within a unique culture will lead to a specialized risk and crisis communication plan accepted by local communities.

Comparing Visual-Only and Visual-Palpation Post-Mortem Lung Scoring Systems in Slaughtering Pigs.

Respiratory diseases continue to pose significant challenges in pig production, and the assessment of lung lesions at the abattoir can provide valuable data for epidemiological investigations and disease surveillance. The evaluation of lung lesions at slaughter is a relatively simple, fast, and straightforward process but variations arising from different abattoirs, observers, and scoring methods can introduce uncertainty; moreover, the presence of multiple scoring systems complicates the comparisons of different studies, and currently, there are limited studies that compare these systems among each other. The objective of this study was to compare validated, simplified, and standardized schemes for assessing surface-related lung lesions in slaughtered pigs and analyze their reliability under field conditions. This study was conducted in a high-throughput abattoir in Italy, where two different scoring methods (Madec and Blaha) were benchmarked using 637 plucks. Statistical analysis revealed a good agreement between the two methods when severe or medium lesions were observed; however, their ability to accurately identify healthy lungs and minor injuries diverged significantly. These findings demonstrate that the Blaha method is more suitable for routine surveillance of swine respiratory diseases, whereas the Madec method can give more detailed and reliable results for the respiratory and welfare status of the animals at the farm level.

Cancer Incidence by Race and Immigration Status in Canada: Value of Enhanced Sociodemographic Data for Disease Surveillance

Abstract Metrics of cancer burden stratified by race can inform tailored prevention strategies. Examining how these metrics, such as incidence, vary by immigration status can provide insight into the drivers of differential cancer risk by race. The conduct of such analyses in Canada has historically been hindered by a lack of sociodemographic data in routine health data sources, including cancer registries. In their recent study, Malagón and colleagues overcome this challenge by using National Cancer Registry data linked to self-reported race and place of birth from the Canadian census. The study provides estimates of cancer incidence for 19 cancer sites across more than 10 racial groups. Compared with the total population, they found that cancer risk tended to be lower among persons belonging to non-White, non-Indigenous racial groups. Exceptions were stomach, liver, and thyroid cancers where incidence rates were higher in minority groups than in the White population. For some cancers and racial groups, incidence was lower irrespective of immigration status, suggesting the healthy immigrant effect may be sustained across generations or that other factors are also at play. The results highlight potential areas for deeper inquiry and underscore the value of sociodemographic data for disease surveillance. See related article by Malagón et al., p. 906

COVID-19 Impact on Lassa Fever Spread and Mortality in Nigeria: Evidence from National Disease Surveillance Data

COVID-19 Impact on Lassa Fever Spread and Mortality in Nigeria: Evidence from National Disease Surveillance Data

Mumps epidemic dynamics in the United States before vaccination (1923–1932)

Mumps is a vaccine-preventable, reemerging, and highly transmissible infectious disease. Widespread vaccination dramatically reduced cases; however, case counts have been increasing over the past 20 years. To provide a quantitative overview of historical mumps dynamics that can act as baseline information to help identify causes of mumps reemergence, we analyzed timeseries of cases reported from 1923 to 1932 in the United States. During that time, 239,230 mumps cases were reported in 70 cities. Larger cities reported annual epidemics and smaller cities reported intermittent, sporadic outbreaks. The critical community size above which transmission continuously occurred was likely between 365,583 and 781,188 individuals but could range as high as 3,376,438 individuals. Mumps cases increased as city size increased, suggesting density-dependent transmission. Using a density-dependent SEIR model, we calculated a mean effective reproductive number (Re) of 1.2. Re varied by city and over time, with periodic high values that could characterize short periods of very high transmission known as superspreading events. Case counts most often peaked in March, with higher-than-average transmission from December through April and showed a correlation with weekly births. While certain city pairs in Midwestern states had synchronous outbreaks, most outbreaks were less synchronous and not driven by distance between cities. This work demonstrates the importance of long-term infectious disease surveillance data and will inform future studies on mumps reemergence and control.

Trends in the rate of regular exercise among adults: results from chronic disease and risk factor surveillance from 2010 to 2018 in Jiangsu, China.

The aims of this study were to estimate the rates of regular exercise and its trends among the adult population in Jiangsu, from 2010 to 2018, China, and to assess associations with sociodemographic factors. Chronic disease and risk factor surveillance data from adults aged ≥18 years were gathered in Jiangsu Province from 2010 to 2018. Rates of regular exercise were calculated after post-stratification weighting, and time trends were compared among participants with different characteristics, including gender, age, urban-rural region, educational level, occupation, annual household income, body mass index (BMI), baseline self-reported chronic diseases, smoking status, alcohol consumption, and region. Multivariable logistic regression analyses were performed to assess the associations of sociodemographic characteristics with regular exercise. A total of 33,448 participants aged 54.05 ± 14.62 years and 55.4% female (8,374 in 2010, 8,302 in 2013, 8,372 in 2015, and 8,400 in 2018) were included in this study. The weighted rate of regular exercise was 12.28% (95% confidence interval [CI]: 9.11-15.45%) in 2010 and 21.47% (95% CI, 17.26-25.69%) in 2018, showing an overall increasing trend (P for trend = 0.009). Nevertheless, stratification analysis showed that the regular exercise rate decreased from 33.79% in 2010 to 29.78% in 2018 among retired adults. Significant associations were observed between regular exercise and age >45 years (45- < 60 years, odds ratio [OR]: 1.24, 95% CI: 1.14-1.34; ≥60 years, OR: 1.20, 95% CI: 1.08-1.34), urban residence (OR: 1.43, 95% CI: 1.32-1.54), higher education (primary, OR: 1.30, 95% CI: 1.16-1.46; secondary, OR: 2.00, 95% CI: 1.79-2.25; college or higher, OR: 3.21, 95% CI: 2.77-3.72), occupation (manual work, OR: 1.52, 95% CI: 1.33-1.73; non-manual work, OR: 1.69, 95% CI: 1.54-1.85; not working, OR: 1.22, 95% CI: 1.03-1.44; retired, OR: 2.94, 95% CI: 2.61-3.30), higher income (¥30,000- < ¥60,000, OR: 1.16, 95% CI: 1.06-1.28; ≥¥60,000, OR: 1.20, 95% CI: 1.10-1.32), higher BMI (overweight, OR: 1.12, 95% CI: 1.05-1.20), self-reported chronic disease at baseline (OR: 1.24, 95% CI:1.16-1.33), former smoking (OR: 1.15, 95% CI: 1.01-1.31) and ever (30 days ago) drinking (OR: 1.20, 95% CI: 1.11-1.29). The rate of regular exercise among adults in Jiangsu Province was low, but this rate increased by 9.17% from 2010 to 2018, showing an upward trend. There were differences in the rate of regular exercise among different sociodemographic factors.

Assessing Public Health Impact of Four Pediatric Pneumococcal Conjugate Vaccination Strategies in the Netherlands.

The 10-valent pneumococcal conjugate vaccine (PCV10, Synflorix) was introduced into the Dutch pediatric national immunization program (NIP) starting in 2011. However, there is substantial pneumococcal disease burden due to increases in non-PCV10 covered serotypes. Higher-valent vaccines for pediatrics (PCV13, PCV15, and PCV20) may alleviate much of the remaining disease burden upon implementation through broader serotype coverage. This article assesses the public health impact of different pediatric vaccination strategies (switching to PCV13, PCV15 or PCV20) versus maintaining PCV10 at different time intervals in the Netherlands. A population-based, decision-analytic model was developed using historical pneumococcal disease surveillance data to forecast future invasive pneumococcal disease (IPD), pneumonia, and otitis media (OM) cases over a 7-year period (2023-2029) under the following strategies: continued use of PCV10, switching to PCV13 in 2023, switching to PCV15 in 2023, and switching to PCV20 in 2024. Scenario analyses were performed to account for uncertainties in future serotype distributions, disease incidence reductions, and epidemiologic parameters. Switching to PCV13 in 2023 was found to avert 26,666 cases of pneumococcal disease compared to continuing PCV10 over a 7-year period (2023-2029). Switching to PCV15 in 2023 was found to avert 30,645 pneumococcal cases over the same period. Switching to PCV20 once available in 2024 was estimated to avert 45,127 pneumococcal cases from 2024-2029. Overall conclusions were maintained after testing uncertainties. For the Dutch pediatric NIP, switching to PCV13 in 2023 would be an effective strategy compared with continued use of PCV10 for averting pneumococcal disease cases. Switching to PCV20 in 2024 was estimated to avert the most pneumococcal disease cases and provide the highest protection. However, in the face of budget constraints and the undervaluation of prevention strategies, it remains challenging to implement higher valent vaccines. Further research is needed to understand the cost-effectiveness and feasibility of a sequential approach.

Association between ambient air pollutants and upper respiratory tract infection and pneumonia disease burden in Thailand from 2000 to 2022: a high frequency ecological analysis

BackgroundA pertinent risk factor of upper respiratory tract infections (URTIs) and pneumonia is the exposure to major ambient air pollutants, with short term exposures to different air pollutants being shown to exacerbate several respiratory conditions.MethodsHere, using disease surveillance data comprising of reported disease case counts at the province level, high frequency ambient air pollutant and climate data in Thailand, we delineated the association between ambient air pollution and URTI/Pneumonia burden in Thailand from 2000 – 2022. We developed mixed-data sampling methods and estimation strategies to account for the high frequency nature of ambient air pollutant concentration data. This was used to evaluate the effects past concentrations of fine particulate matter (PM2.5), sulphur dioxide (SO2), and carbon monoxide (CO) and the number of disease case count, after controlling for the confounding meteorological and disease factors.ResultsAcross provinces, we found that past increases in CO, SO2, and PM2.5 concentration were associated to changes in URTI and pneumonia case counts, but the direction of their association mixed. The contributive burden of past ambient air pollutants on contemporaneous disease burden was also found to be larger than meteorological factors, and comparable to that of disease related factors.ConclusionsBy developing a novel statistical methodology, we prevented subjective variable selection and discretization bias to detect associations, and provided a robust estimate on the effect of ambient air pollutants on URTI and pneumonia burden over a large spatial scale.

Healthcare personnel with laboratory-confirmed mpox in California

Objectives: Few reports have been published about the transmission of mpox in healthcare settings. During the 2022 multinational outbreak, the California Department of Public Health (CDPH) conducted a systematic review of healthcare personnel (HCP) with mpox, including their community and occupational exposures, to understand the transmission risk in healthcare settings. We also sought to inform return-to-work protocols by describing the frequency of HCP working while symptomatic for mpox and identifying occurrences of secondary transmission from infected HCP to patients. Methods: We analyzed surveillance data for laboratory-confirmed mpox cases in California with symptom onset from May 17 to September 30, 2022, collected by investigators at local health departments and reported to the CDPH. The reported data were supplemented by review of free-text variables, interview notes, and other files uploaded to state and county disease surveillance data registries. We identified HCP as all persons working in healthcare settings with potential for direct or indirect exposure to patients or infectious materials, including clinical and nonclinical staff but excluding remote workers. Results: The CDPH received reports of 3,176 mpox cases during the study period: 109 were HCP. Of the 109 HCP identified from 19 counties, 78 (72%) were aged 30–49 years, 102 (94%) were male, and 43 (39%) were Hispanic or Latino. Also, 29 HCP (27%) had received at least 1 dose of the JYNNEOS vaccine. Occupations requiring frequent physical interactions with patients were reported for 66 individuals (61%). During interviews with local health department investigators, nearly all HCP (n = 98, 90%) reported potential or confirmed sources of community exposure; 1 had confirmed occupational exposure with symptom onset 9 days after a sharps injury acquired during collection of an mpox specimen for testing. Of the 60 HCP who provided information about the days they worked, 35 (58%) worked while symptomatic, for a mean of 3.14 days (median, 2; IQR, 3). Also, 2 HCP worked for 12 days after symptom onset. No secondary cases of mpox were associated with HCP reported to the CDPH. Conclusions: This analysis suggests that HCP are more likely to be exposed to mpox in community settings than healthcare settings. The findings support recommendations against sharps use for mpox specimen collection. Although transmission between symptomatic HCP and patients was not reported, HCP can decrease opportunities for mpox transmission by closely monitoring themselves for symptoms after potential exposures and staying home from work if symptoms develop.Disclosures: None

Burden of Rotavirus Diarrhoea in Children in Abuja

Background: Diarrhoea is the second leading cause of death in children. Nigeria has the continent’s highest mortality due to diarrhoeal diseases with little information on specific causes and the proportion affected by rotavirus infection. The main objectives of this study were to describe the features of young children with diarrhoea, with and without rotavirus, in Abuja the Federal Capital Territory. Materials and Methods: Retrospective review of local hospital activity data related to diarrhoea was retrieved from General Hospitals in Abuja. Then a one-year prospective descriptive study of children under 5 years of age with acute diarrhoea was conducted from September 2012 to August 2013. Children with acute diarrhoea attending three government hospitals and one private hospital were recruited. Children without diarrhoea were recruited as the control group. Faecal specimens were transported in cold chain boxes from Nigeria and stored at -80 °C at the Institute of Global Health, virology section of the University of Liverpool, where all laboratory work was performed. Results: Hospital records were poorly preserved and did not provide meaningful data for trend analyses or disease surveillance. 1331 participants were enrolled in this prospective study. Stool samples were collected from 1242 (93.3%) participants, of whom 957 (77.0%) were ambulatory, 123 (9.9%) hospitalised and 160 (12.8%) controls without diarrhoea. 881 and 450 children with diarrhoea were recruited from government and the private hospitals, respectively. The median age of the children was 8 months in the ambulatory and 9.5 months in the hospitalized group (p&lt;0.05). A total of 209 (16.8%) children were vaccinated, 858 (69.1%) were unvaccinated, and 174 (14.0%) had an unclear vaccination status. Rotavirus ELISA was positive in 123 (11.4%) children with diarrhoea and 2 (1.2%) controls. Among children with diarrhoea, 92 (10.4%) of 881 children attending government hospitals had rotavirus, compared to 33 (7.3%) of 450 children attending a private hospital (p&lt;0.001) where a vaccination program had been in place. The peak months for rotavirus infection were November and February. The efficacy of Rotarix® RV1 vaccine in preventing rotavirus diarrhoea was indirectly assessed to be 64.5%. Conclusion: Rotavirus is an important pathogen in children, especially in unvaccinated children in Abuja. The introduction of a rotavirus vaccine is highly desirable in Nigeria, but this is still awaited. Local and national infrastructure are inadequate for basic surveillance of diarrhoeal disease, and this will have to be improved, together with access to virological stool testing, to monitor the planned vaccine program. The retrospective studies reported here provide indirect evidence of vaccine efficacy in Abuja but need prospective confirmation.