BACKGROUND: Lower Respiratory Tract Infections (LRTI) pose a serious threat to older adults but may be underdiagnosed due to atypical presentations. Here we assess LRTI symptom profiles and syndromic (symptom-based) case ascertainment in older (≥ 65y) as compared to younger adults (< 65y).
METHODS: We included adults (≥ 18y) with confirmed LRTI admitted to two acute care Trusts in Bristol, UK from 1st August 2020- 31st July 2022. Logistic regression was used to assess whether age ≥ 65y reduced the probability of meeting syndromic LRTI case definitions, using patients\' symptoms at admission. We also calculated relative symptom frequencies (log-odds ratios) and evaluated how symptoms were clustered across different age groups.
RESULTS: Of 17,620 clinically confirmed LRTI cases, 8,487 (48.1%) had symptoms meeting the case definition. Compared to those not meeting the definition these cases were younger, had less severe illness and were less likely to have received a SARS-CoV-2 vaccination or to have active SARS-CoV-2 infection. Prevalence of dementia/cognitive impairment and levels of comorbidity were lower in this group. After controlling for sex, dementia and comorbidities, age ≥ 65y significantly reduced the probability of meeting the case definition (aOR = 0.67, 95% CI:0.63-0.71). Cases aged ≥ 65y were less likely to present with fever and LRTI-specific symptoms (e.g., pleurisy, sputum) than younger cases, and those aged ≥ 85y were characterised by lack of cough but frequent confusion and falls.
CONCLUSIONS: LRTI symptom profiles changed considerably with age in this hospitalised cohort. Standard screening protocols may fail to detect older and frailer cases of LRTI based on their symptoms.

UNASSIGNED: CYD-TDV (Dengvaxia®) was the first dengue vaccine approved, launched in Brazil in 2015 for individuals aged 9-44 years. We aimed to estimate the effectiveness of CYD-TDV in preventing symptomatic dengue cases during a campaign targeting individuals aged 15-27 years in selected municipalities in Paraná, Brazil. Additionally, we examined whether a history of dengue, as recorded by the surveillance system, modified the vaccine\'s effectiveness.
UNASSIGNED: We conducted a case-cohort analysis comparing the frequency of vaccination, with at least one dose of CYD-TDV, in individuals with dengue confirmed by RT-PCR, identified by the surveillance system during 2019 and 2020, with the vaccination coverage in the target population. Moreover, in a case-control design using weighted controls, we assessed the documented history of dengue as a modifier of the vaccine\'s effectiveness. We used a logistic random-effects regression model, with data clustered in municipalities and incorporating covariates such as the incidence of dengue before the campaign, age, and sex. We calculated vaccine effectiveness (VE) as (1-relative risk) x 100%.
UNASSIGNED: 1869 dengue cases were identified, which had a vaccination frequency significantly lower than the overall vaccination coverage in the target population (50.3% vs. 57.2%, respectively; overall VE: 21.3%; 95% confidence interval [CI]: 13.4%-28.4%). In individuals with a documented history of dengue, vaccination had a VE of 71% (95% CI: 58%-80%) in reducing the incidence of dengue. However, vaccination was not associated with a significant reduction in the overall dengue case risk in individuals without a documented history of dengue (VE: 12%; 95% CI: -21% to 36%). In this last stratum, vaccination was associated with reduced cases due to DENV-1 and DENV-4, but an excess of DENV-2 cases.
UNASSIGNED: Vaccination led to a significant reduction in reported dengue cases within the target population. The case-control design suggested that this reduction was primarily driven by the benefits observed in individuals with a documented history of dengue. In endemic regions with limited serological testing facilities, a previous history of dengue diagnosis recorded by epidemiological surveillance could be used to triage candidates for CYD-TDV vaccination.
UNASSIGNED: Research supported by Sanofi.

The sustained instability in Afghanistan, along with ongoing disease outbreaks and the impact of the COVID-19 pandemic, has significantly affected the country.During the COVID-19 pandemic, the country\'s detection and response capacities faced challenges. Case identification was done in all health facilities from primary to tertiary levels but neglected cases at the community level, resulting in undetected and uncontrolled transmission from communities. This emphasizes a missed opportunity for early detection that Event-Based Surveillance (EBS) could have facilitated.Therefore, Afghanistan planned to strengthen the EBS component of the national public health surveillance system to enhance the capacity for the rapid detection and response to infectious disease outbreaks, including COVID-19 and other emerging diseases. This effort was undertaken to promptly mitigate the impact of such outbreaks.We conducted a landscape assessment of Afghanistan\'s public health surveillance system to identify the best way to enhance EBS, and then we crafted an implementation work plan. The work plan included the following steps: establishing an EBS multisectoral coordination and working group, identifying EBS information sources, prioritizing public health events of importance, defining signals, establishing reporting mechanisms, and developing standard operating procedures and training guides.EBS is currently being piloted in seven provinces in Afghanistan. The lessons learned from the pilot phase will support its overall expansion throughout the country.

In Japan, based on the National Epidemiological Surveillance of Infectious Diseases (NESID) Program, influenza cases from ~5,000 sentinel sites are monitored weekly as part of influenza surveillance (as number of influenza cases/sentinel site). One limitation is that the number of influenza tests conducted is not reported. Separately, the National Hospital Organization (NHO), with ~140 hospitals, routinely publishes three indicators: number of influenza tests, influenza-positive case counts, and test positivity. We used NESID and NHO data from April 2011 to June 2022 to assess the usefulness of multiple indicators to monitor influenza activity. Temporal trends of the NHO and NESID indicators were similar, and NHO indicator levels well-correlated with those of the NESID indicator. Influenza positivity in the NHO data, however, showed an earlier rise and peak time compared to the NESID indicator. Importantly, through the non-epidemic summer periods and the coronavirus disease 2019 pandemic, a sizable number of influenza tests continued to be done at NHO hospitals, with results showing considerably low case counts and test positivity. These data show that a relatively small number of sentinel sites is sufficient to monitor influenza activity nationally, and, that utilizing multiple indicators can increase our confidence in situational awareness and data interpretations.

BACKGROUND: Gamma-hydroxybutyrate (GHB) use is associated with high risk of accidental overdose. This study examined the pre-hospital circumstances, demographic characteristics and clinical outcomes of analytically confirmed GHB emergency department (ED) presentations in Western Australia (WA).
METHODS: This case series was conducted across three WA EDs involved in the Emerging Drugs Network of Australia, from April 2020 to July 2022. Patient demographics, pre-hospital drug exposure circumstances and ED presentation and outcome characteristics were collected from ambulance and hospital medical records of GHB-confirmed cases.
RESULTS: GHB was detected in 45 ED presentations. The median age was 34 years and 53.3% (n = 24) were female. Most patients arrived at the ED by ambulance (n = 37, 85.7%) and required immediate emergency care (Australasian Triage Score 1 or 2 = 97.8%). One-third of patients were admitted to intensive care (n = 14, 31.1%). Methylamphetamine was co-detected in 37 (82.2%) GHB-confirmed cases. Reduced conscious state was indicated by first recorded Glasgow Coma Scale of ≤8 (n = 29, 64.4%) and observations of patients becoming, or being found, \'unresponsive\' and \'unconscious\' in various pre-hospital settings (n = 28, 62.2%). \'Agitated\' and/or \'erratic\' mental state and behavioural observations were recorded in 20 (44.4%) cases.
CONCLUSIONS: Analytically verified data from ED presentations with acute toxicity provides an objective information source on drug use trends and emerging public health threats. In our study, patients presenting to WA EDs with GHB intoxication were acutely unwell, often requiring intensive care treatment. The unexpectedly high proportion of female GHB intoxications and methylamphetamine co-ingestion warrants further exploration.

Disease transmission is dependent on a variety of factors, including the characteristics of an event, such as crowding and shared accommodations, the potential of participants having prolonged exposure and close contact with infectious individuals, the type of activities, and the characteristics of the participants, such as their age and immunity to infectious agents [1-3]. Effective control of outbreaks of infectious diseases requires rapid diagnosis and intervention in high-risk settings. As a result, syndromic and event-based surveillance may be used to enhance the responsiveness of the surveillance system [1]. In public health, surveillance is collecting, analyzing, and interpreting data across time to inform decision-making and aid policy implementation [1]. In this review article we aimed to provide an overview of the principles, types, uses, advantages, and limitations of surveillance systems and to highlight the importance of early warning systems in response to the information received by disease surveillance. The study conducted a comprehensive literature search using several databases, selecting, and reviewing 78 articles that covered different types of surveillance systems, their applications, and their impact on controlling infectious diseases. The article also presents a case study from the Hajj gathering, which highlighted the development, evaluation, and impact of early warning systems on response to the information received by disease surveillance. The study concludes that ongoing disease surveillance should be accompanied by well-designed early warning and response systems, and continuous efforts should be invested in evaluating and validating these systems to minimize the risk of reporting delays and reducing the risk of outbreaks.

Shigellosis is spread through the fecal-oral route, including sexual activity. The Centers for Disease Control and Prevention recommends collecting a sexual history from people diagnosed with shigellosis to enhance the understanding of its epidemiology and outbreak detection and the design of disease prevention messaging, although individual jurisdictions decide if and how this is done. Moreover, enteric disease interviewers typically receive in-depth general interviewing training, but often not sexual history question training. The goal of this project was to inform national practices around sexual history questions asked during shigellosis interviews by collecting information from U.S. state health agencies and evaluating sexual history data from people diagnosed with shigellosis in Colorado. From November 2021 to January 2022, information on sexual history questions asked of persons with reported shigellosis and accompanying training resources were collected from U.S. state health departments. Data completeness and quality of shigellosis sexual history questions from Colorado\'s notifiable disease database from 2018 to 2022 were also evaluated. Of 48 states, 54% reported routinely asking all adults about their sexual history during shigellosis interviews. Of 44 states, 18% indicated having accompanying training materials for interviewers. In Colorado, the proportion of unknown/missing responses to questions about recent sexual contact with male and female partners was lower for males (3.3% unknown and 3.3% missing) than females (5.4% and 6.2%) and highest among those 66 years and older (6.7% and 10%). Among those reporting new sexual partners, 93.5% indicated how they met. The evaluation of Colorado data demonstrates that routine collection of complete, high-quality, actionable sexual history data from all adults with reported shigellosis is feasible. Nearly half of the responding states indicated not doing so, and few had training resources. We recommend training enteric disease interviewers to routinely ask all adults with reported shigellosis about their sexual history, including new partner meeting location.

UNASSIGNED: Determine the economic cost or benefit of expanding electronic case reporting (eCR) for 29 reportable conditions beyond the initial eCR implementation for COVID-19 at an academic health center.
UNASSIGNED: The return on investment (ROI) framework was used to quantify the economic impact of the expansion of eCR from the perspective of an academic health system over a 5-year time horizon. Sensitivity analyses were performed to assess key factors such as personnel cost, inflation, and number of expanded conditions.
UNASSIGNED: The total implementation costs for the implementation year were estimated to be $5031.46. The 5-year ROI for the expansion of eCR for the 29 conditions is expected to be 142% (net present value of savings: $7166). Based on the annual ROI, estimates suggest that the savings from the expansion of eCR will cover implementation costs in approximately 4.8 years. All sensitivity analyses yielded a strong ROI for the expansion of eCR.
UNASSIGNED: Our findings suggest a strong ROI for the expansion of eCR at UHealth, with the most significant cost savings observed implementing eCR for all reportable conditions. An early effort to ensure data quality is recommended to expedite the transition from parallel reporting to production to improve the ROI for healthcare organizations. This study demonstrates a positive ROI for the expansion of eCR to additional reportable conditions beyond COVID-19 in an academic health setting, such as UHealth. While this evaluation focuses on the 5-year time horizon, the potential benefit could extend further.

Social distancing interrupted transmission patterns of contact-driven infectious agents such as norovirus during the Covid-19 pandemic. Since routine surveillance of norovirus was additionally disrupted during the pandemic, traditional naïve forecasts that rely only on past public health surveillance data may not reliably represent norovirus activity. This study investigates the use of statistical modelling to predict the number of norovirus laboratory reports in England 4-weeks ahead of time before and during Covid-19 pandemic thus providing insights to inform existing practices in norovirus surveillance in England. We compare the predictive performance from three forecasting approaches that assume different underlying structure of the norovirus data and utilized various external data sources including mobility, air temperature and relative internet searches (Time Series and Regularized Generalized Linear Model, and Quantile Regression Forest). The performance of each approach was evaluated using multiple metrics, including a relative prediction error against the traditional naive forecast of a five-season mean. Our data suggest that all three forecasting approaches improve predictive performance over the naïve forecasts, especially in the 2020/21 season (30-45% relative improvement) when the number of norovirus reports reduced. The improvement ranged from 7 to 22% before the pandemic. However, performance varied: regularized regression incorporating internet searches showed the best forecasting score pre-pandemic and the time series approach achieved the best results post pandemic onset without external data. Overall, our results demonstrate that there is a significant value for public health in considering the adoption of more sophisticated forecasting tools, moving beyond traditional naïve methods, and utilizing available software to enhance the precision and timeliness of norovirus surveillance in England.

We determined correlations between SARS-CoV-2 load in untreated water and COVID-19 cases and patient hospitalizations before the Omicron variant (September 2020-November 2021) at 2 wastewater treatment plants in the Regional Municipality of Peel, Ontario, Canada. Using pre-Omicron correlations, we estimated incident COVID-19 cases during Omicron outbreaks (November 2021-June 2022). The strongest correlation between wastewater SARS-CoV-2 load and COVID-19 cases occurred 1 day after sampling (r = 0.911). The strongest correlation between wastewater load and COVID-19 patient hospitalizations occurred 4 days after sampling (r = 0.819). At the peak of the Omicron BA.2 outbreak in April 2022, reported COVID-19 cases were underestimated 19-fold because of changes in clinical testing. Wastewater data provided information for local decision-making and are a useful component of COVID-19 surveillance systems.