Surveillance Data Research Articles

Comprehensive evaluation of malaria reactive surveillance and response strategies in Lao People’s Democratic Republic: a mixed-methods study

ObjectivesTo achieve malaria elimination by 2030, the Lao People’s Democratic Republic (PDR) adopted a reactive surveillance and response (RASR) strategy of malaria case notification within 1 day, case investigation and...

Epidemiological analysis of event-based surveillance data of Crimean-Congo Hemorrhagic Fever (CCHF) outbreaks across Balochistan Province, Pakistan, from 2000 to August 2021

Epidemiological analysis of event-based surveillance data of Crimean-Congo Hemorrhagic Fever (CCHF) outbreaks across Balochistan Province, Pakistan, from 2000 to August 2021

Community-Engaged Survey Approach to Pandemic Impacts on Marginalized Communities, Massachusetts, 2020-2021.

Objectives. To describe how an innovative, community-engaged survey illuminated previously unmeasured pandemic inequities and informed health equity investments. Methods. The methodological approach of Massachusetts' COVID-19 Community Impact Survey, a cross-sectional online survey, was driven by key health equity principles: prioritizing community engagement, gathering granular and intersectional data, capturing root causes, elevating community voices, expediting analysis for timeliness, and creating data-to-action pathways. Data collection was deployed statewide in 11 languages from 2020 to 2021. Results. The embedded equity principles resulted in a rich data set and enabled analyses of populations previously undescribed. The final sample included 33 800 respondents including unprecedented numbers of populations underrepresented in traditional data sources. Analyses indicated that pandemic impacts related to basic needs, discrimination, health care access, workplace protections, employment, and mental health disproportionately affected these priority populations, which included Asian American/Pacific Islanders and parents. Conclusions. Equity-centered data approaches allow for analyses of populations previously invisible in surveillance data, enable more equitable public health action, and are both possible and necessary to deploy in state health departments. (Am J Public Health. 2024;114(S7):S599-S609. https://doi.org/10.2105/AJPH.2024.307800).

Pathological Characteristics, Management, and Prognosis of Rectal Neuroendocrine Tumors: A Retrospective Study from a Tertiary Hospital.

Rectal neuroendocrine tumors (rNENs) are rare, constituting 1-2% of rectal tumors, and are often asymptomatic, leading to challenges in early diagnosis. Current management guidelines recommend endoscopic resection for small lesions and surgical intervention for larger or high-risk tumors. This study aims to retrospectively analyze the pathological characteristics, management, and prognosis of rNEN patients. Data from the Neuroendocrine Tumor Registry at a tertiary hospital in Milan, Italy from 2005 to 2023 were retrospectively analyzed. Patient demographics, disease characteristics, pathology findings, treatment details, and surveillance data were collected. Statistical analyses included descriptive statistics, multivariable binary logistic regression, and Kaplan-Meier survival analysis. Forty-five patients were included, 53.3% male with a mean age of 57.5 years. Most patients were asymptomatic, with incidental diagnosis during colonoscopy. Endoscopic excision was the primary treatment modality (77.8%), with surgical resection reserved for incomplete or inappropriate endoscopic resections. Disease progression occurred in 13 patients (28.9%), with tumor-related mortality of 22.2%. Kaplan-Meier analysis showed 5- and 10-year survival rates of 68.8% and 59.1%, respectively, with corresponding progression-free survival rates of 72.8% and 54.0%. Tumor stage was significantly associated with disease progression on multivariable analysis (OR = 7.230, p = 0.039). This study highlights the heterogeneous presentation and prognosis of rNENs, with a substantial proportion diagnosed incidentally. Endoscopic management was predominantly utilized, aligning with current guidelines for localized tumors. Tumor stage emerged as a significant predictor of disease progression, emphasizing the importance of accurate staging for optimal management. Further research is warranted to refine management protocols and validate these findings.

Evaluation of Rhode Island's Early Geographic COVID-19 Vaccine Prioritization Policy.

Objectives. To determine whether geographic prioritization of limited COVID-19 vaccine supply was effective for reducing geographic disparities in case rates. Methods. Rhode Island allocated a portion of the initial COVID-19 vaccine supply to residents of Central Falls, a community already affected by structural policies and inadequate systems that perpetuate health inequities and experiencing disproportionately high COVID-19 morbidity and mortality. The policy was implemented with a culturally and linguistically appropriate community engagement plan and was intended to reduce observed disparities. Using a Bayesian causal analysis with population surveillance data, we evaluated the impact of this prioritization policy on recorded cases over the subsequent 16 weeks. Results. Early geographic prioritization of Central Falls accelerated vaccine uptake, averting an estimated 520 cases (95% confidence interval = 22, 1418) over 16 weeks and reducing cases by approximately 34% during this period (520 averted vs 1519 expected without early prioritization). Conclusions. Early geographic prioritization increased vaccine uptake and reduced cases in Central Falls, thereby reducing geographic disparities. Public Health Implications. Public health institutions should consider geographic prioritization of limited vaccine supply to reduce geographic disparities in case rates. (Am J Public Health. 2024;114(S7):S580-S589. https://doi.org/10.2105/AJPH.2024.307741).

Trends in the hand hygiene practices using alcohol-based hand rubs in Japanese hospitals before and after the novel coronavirus pandemic: an observational study using national surveillance data

Healthcare-associated infections (HAIs) are a global concern in healthcare facilities, and hand hygiene (HH) using alcohol-based hand rubs (ABHR) is fundamentally crucial for their prevention. While previous studies report improvements in HH compliance amid the COVID-19 pandemic, the real situation in Japanese medical settings remains unclear. This observational study sought data from the Japanese national surveillance, focusing on ABHR use in hospitals before and after the COVID-19 pandemic. Data were retrieved from facilities certified to receive the Additional Healthcare Reimbursements for Infection Prevention and Control I. The study spanned five years (2019-2023), segmented quarterly, and employed Joinpoint regression analysis to assess the annual percentage change (APC). Overall, ABHR use per patient per day significantly increased both in critical care units and general wards amid the pandemic. However, the APC in the critical care units demonstrated a downward trend from Q4 of 2021 to Q1 of 2023, and ABHR use in general wards remained below the amount of WHO recommendations. This trend analysis highlighted recent patterns of ABHR use in Japanese hospitals by comparing pre- and post-COVID-19 periods. Although increases in ABHR use were observed over time, sustained efforts to promote HH compliance are necessary, particularly in general wards.

Modeling the potential public health impact of different vaccination strategies with an adapted vaccine in South Africa

ABSTRACT Background COVID-19 vaccines adapted to newly emerging circulating variants are necessary to better protect the population due to the evolving nature of the SARS-CoV-2 virus. Research Design and Methods The South African population was stratified by age and risk (defined by comorbidities such as diabetes, obesity, smoking, cancer, and asthma), and HIV status. The outcomes of different vaccination strategies based on age, risk, and HIV status were estimated using a Markov-decision tree model based on age-specific inputs derived from the literature and South African surveillance data. Results Vaccinating older adults and those with comorbidities was estimated to avert 111,179 infections 18,281 hospitalizations, and 3,868 deaths, resulting in savings of ZAR 1,260 million (USD 67 million) and ZAR 3,205 million (USD 170 million) in direct and indirect costs, respectively. Similar results were obtained when considering strategies targeting older adults and the HIV population. Expanding vaccination to 75% of the standard-risk population prevented more infections (401%), hospitalizations (167%), and deaths (67%) and increased the direct (232%) and indirect (455%) cost savings compared to the base case. Conclusions Implementing widespread vaccination strategies that utilize a vaccine adapted to the prevailing circulating variant in South Africa would result in significant public health and economic gains.

Interventions to Mitigate the Impact of COVID-19 Among People Experiencing Sheltered Homelessness: Chicago, Illinois, March 1, 2020-May 11, 2023.

Objectives. To compare the incidence, case-hospitalization rates, and vaccination rates of COVID-19 between people experiencing sheltered homelessness (PESH) and the broader community in Chicago, Illinois, and describe the impact of a whole community approach to disease mitigation during the public health emergency. Methods. Incidence of COVID-19 among PESH was compared with community-wide incidence using case-based surveillance data from March 1, 2020, to May 11, 2023. Seven-day rolling means of COVID-19 incidence were assessed for the overall study period and for each of 6 distinct waves of COVID-19 transmission. Results. A total of 774 009 cases of COVID-19 were detected: 2579 among PESH and 771 430 in the broader community. Incidence and hospitalization rates per 100 000 in PESH were more than 5 times higher (99.84 vs 13.94 and 16.88 vs 2.14) than the community at large in wave 1 (March 1, 2020-October 3, 2020). This difference decreased through wave 3 (March 7, 2021-June 26, 2021), with PESH having a lower incidence rate per 100 000 than the wider community (8.02 vs 13.03). Incidence and hospitalization of PESH rose again to rates higher than the broader community in waves 4 through 6 but never returned to wave 1 levels. Throughout the study period, COVID-19 incidence among PESH was 2.88 times higher than that of the community (70.90 vs 24.65), and hospitalization was 4.56 times higher among PESH (7.51 vs 1.65). Conclusions. Our findings suggest that whole-community approaches can minimize disparities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission between vulnerable populations and the broader community, and reinforce the benefits of a shared approach that include multiple partners when addressing public health emergencies in special populations. (Am J Public Health. 2024;114(S7):S590-S598. https://doi.org/10.2105/AJPH.2024.307801).

Development of a clinical prediction score for Ebola virus disease screening at triage centers in the Democratic Republic of the Congo.

The 2018-2020 Ebola virus disease (EVD) outbreak in the Democratic Republic of the Congo (DRC) was the largest since the disease's discovery in 1976. Rapid identification and isolation of EVD patients are crucial during triage. This study aimed to develop a clinical prediction score for EVD using clinical and epidemiological predictors. We conducted a retrospective cross-sectional study using surveillance data from EVD outbreak, collected during routine clinical care at the Ebola Transit Center (ETC) in Beni, DRC, from 2018 to 2020. The Spiegelhalter and Knill-Jones method was used for score development, including potential predictors with an adjusted likelihood ratio above 2 or below 0.50. Validation was performed using a dataset previously published in PLOSOne by Tshomba et al. Among 3725 patients screened, 3698 fulfilled the inclusion criteria, with 571 (15.4%) testing positive for EVD via RT-PCR Test. Seven predictive factors were identified: asthenia, sore throat, conjunctivitis, bleeding gums, hematemesis, contact with a sick person, and contact with a traditional healer. The prediction score achieved an Area under the receiver operating characteristic (AUROC) of 0.764, with 81.4% sensitivity and 53.6% specificity at a -1 cutoff. External validation demonstrated an AUROC of 0.766, with 80.8% sensitivity and 41.4% specificity at the -1 cutoff. Our study developed a screening tool to assess the risk of suspected patients developing EVD and being admitted to ETUs for RT-PCR testing and treatment. External validation results affirmed the model's reliability and generalizability in similar settings, suggesting its potential integration into clinical practice. Given the severity and urgency of EVD as well as the risk nosocomial EVD transmission, it is essential to continuously update these models with real-time data on symptoms, disease progression, patient outcomes and validated RDT during EVD outbreaks. This approach will enhance model accuracy, enabling more precise risk assessments and more effective outbreak management.

Drug-resistant tuberculosis care and treatment outcomes over the last 15 years in Ethiopia: Results from a mixed-method review of trends.

Drug resistant tuberculosis (DR-TB) remains a global challenge with about a third of the cases are not detected. With the recent advances in the diagnosis and treatment follow-up of DR-TB, there have been improvements with treatment success rates. However, there is limited evidence on the successful models of care that have consistently registered good outcomes. Our aim was to assess Ethiopia's experience in scaling up an ambulatory, decentralized model of care while managing multiple regimen transition processes and external shocks. This was a cross-sectional, mixed-method study. For the quantitative data, we reviewed routine surveillance data for the period 2009-2022 and collected additional data from publicly available reports. We then analyzed the data descriptively. Qualitative data were collected from program reports, quarterly presentations, minutes of technical working group meetings, and clinical review committee reports and analyzed thematically. The number of DR-TB treatment initiating centers increased from 1 to 67, and enrollment increased from 88 in 2010 to 741 in 2019, but declined to 518 in 2022. A treatment success rate (TSR) of over 70% was sustained. The decentralized and ambulatory service delivery remained the core service delivery model. The country successfully navigated multiple regimen transitions, including the recently introduced six-month short oral regimen. Several challenges remain, including the lack of strong and sustainable specimen transportation system, lack of established systems for timely tracing and linking of missed DR-TB cases, and data quality issues. Ethiopia scaled up a decentralized ambulatory model of care, kept up to date with recent developments in treatment regimens, and maintained a high TSR, despite the influence of multiple external challenges. The recent decline in case notification requires a deeper look into the underlying reasons. The feasibility of fully integrating DR-TB treatment and follow up at community level should be explored further.

Effect of nirsevimab on hospitalisations for respiratory syncytial virus bronchiolitis in France, 2023–24: a modelling study

Respiratory syncytial virus (RSV) is a major cause of hospitalisations and deaths among infants worldwide. France was one of the first countries to implement a national programme (beginning on Sept 15, 2023) for administration of nirsevimab, a single-dose long-acting monoclonal antibody treatment, to infants born on or after Feb 6, 2023, to prevent lower respiratory tract infection caused by RSV. We aimed to estimate the effectiveness of nirsevimab and the number of hospitalisations averted in children younger than 24 months in real-world settings. In this modelling study, we developed an age-structured deterministic model characterising RSV transmission as well as plausible scenarios for the administration of nirsevimab doses based on maternity ward and community pharmacy supply data. We retrospectively estimated nirsevimab effectiveness in infants younger than 24 months during the 2023-24 RSV season in France (excluding overseas territories) and the number of averted hospitalisations for RSV bronchiolitis occurring after emergency department visits, by calibrating the model to hospital and virological surveillance data from Aug 21, 2017, to Feb 4, 2024, alongside serological data from a previous cross-sectional study. To assess the robustness of our estimates, we conducted sensitivity analyses in which we modified our assumptions about the number of doses administered, the reconstruction of the number of RSV-associated hospitalisations for bronchiolitis, the duration of maternal and post-infection immunity to RSV, and the number of contacts in children aged 0-2 months. We estimated that nirsevimab administration prevented 5800 (95% credible interval 3700-7800) RSV-associated hospitalisations for bronchiolitis after emergency department visits among children younger than 24 months, including 4200 (2900-5600) hospitalisations among those aged 0-2 months, between Sept 15, 2023 (the date nirsevimab was introduced), and Feb 4, 2024-a 23% (16-30) reduction in the total number of hospitalisations and a 35% (25-44) reduction in the 0-2 months age group, compared with the scenario without administration. In our baseline scenario, in which we estimated that 215 000 doses of nirsevimab were administered by Jan 31, 2024, the estimated effectiveness against RSV-associated hospitalisations for bronchiolitis was 73% (61-84), corresponding to one hospitalisation averted for every 39 (26-54) doses administered. In sensitivity analyses, nirsevimab remained effective against RSV-associated hospitalisations for bronchiolitis after emergency department attendance. Our findings show that nirsevimab administration campaigns could effectively reduce the RSV-related hospital burden of bronchiolitis in children younger than 24 months. European Commission, Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases programme, and INCEPTION project.

Malaria reporting timeliness analysis and factors associated with delayed notification, 2018-2022, Nepal.

In order to monitor public health trends and identify disease outbreaks early, efficient and reliable notification and surveillance systems are essential. Nepal uses a 1-3-7 malaria surveillance approach. The Short Message System (SMS) -based system for timely notification has been established. However, knowledge gaps exist regarding the timeliness of notification, treatment initiation, and case-based investigations. Hence, this study identifies the timeliness of notification and factors associated with delayed notification. This study used a cross-sectional approach and used secondary malaria surveillance data from Nepal's national malaria elimination program for the period of 2018 to 2022. The study revealed that the majority (79.9%) of malaria cases were male, with a male-to-female ratio of 3.96:1. Occupation was found to be significantly associated with delayed notification. Repatriate workers had 0.60 times lower odds of experiencing delayed notification compared to the reference occupation. Similarly, individuals diagnosed in the Sudurpaschim and Lumbini provinces had significantly lower odds (0.48 and 0.38, respectively) of encountering delayed notification compared to the reference province. Furthermore, relying on a single laboratory tool for malaria diagnosis (either RDT or microscopy only) was significantly associated with delayed notification. Individuals diagnosed solely with RDT or microscopy had 2.04 and 1.79 times higher odds of experiencing delayed notification, respectively, compared to those diagnosed using both laboratory tools. This study provides insight into the timeliness of surveillance system approach by assessing delayed notification and the factors associated with it. No delays are identified in median notification, treatment time and in case investigation. Improvement in the timeliness of malaria reporting over the years was observed. Provinces with high burden of malaria and repatriate workers showed lower delayed notification and conversely, cases diagnosed with single laboratory tool showed delayed notification time.

Lifestyle Differences in the Metabolic Comorbidity Score of Adult Population From South Asian Countries: A Cross-Sectional Study

BackgroundMetabolic comorbidities are involved in the development and progression of non-communicable diseases (NCDs). There is convincing evidence that lifestyles are important contributors to metabolic comorbidities. This study measured the metabolic comorbidity score of South Asian adults, and identified its relationship with lifestyles. MethodsWe studied five South Asian countries including Afghanistan, Bangladesh, Bhutan, Nepal, and Sri Lanka, using WHO's Stepwise approach to NCD risk factor surveillance data between 2014 and 2019. This was a nationally representative and cross-sectional survey on participants aged 15-69 years old. The sample size was 27,616. The outcome was metabolic comorbidity score, calculated based on total cholesterol, fasting plasma glucose, blood pressure, and abdominal obesity. Total metabolic comorbidity score of each participant varied between 0-8. It was then divided into three ranges – the lowest range (total metabolic comorbidity score <3), medium range (total metabolic comorbidity score ≥3 & ≤5), and the highest range (total metabolic comorbidity score ≥6). Based on the outcome of non-parametric receiver operating characteristics analysis, the medium and the highest range together was considered as higher metabolic comorbidity score. The lowest range was considered as lower metabolic comorbidity score. The higher metabolic comorbidity score was coded as “1”and the lower metabolic comorbidity score was coded as “0”. Thus, the outcome variable, metabolic comorbidity score, became a binary variable. Exposures included physical inactivity (<150 minutes of MVPS /week), high daily sedentary time (≥ 9 hours/day), use of tobacco (present or past smoking or daily use of smokeless tobacco products), and consumption of alcohol (at least once/month in the last one year). Binomial logistic regression model produced the odds ratios (OR) with corresponding 95% confidence intervals (CI). ResultsThe prevalence of higher metabolic comorbidity score was 34% among South Asian adults, 25% among the male respondents and 41% among the female respondents. Participants who were physically inactive (OR, 1.26; 95% CI, 1.17-1.36), had high sedentary time (OR, 1.24; 95% CI, 1.11-1.33), and consumed alcohol (OR, 1.40; 95% CI, 1.23-1.53) showed higher metabolic comorbidity score compared with the participants who were physically active, had low sedentary time and did not consume alcohol respectively. However, we found an inverse association (OR, 0.75; 95% CI, 0.71-0.81) between the use of tobacco and metabolic comorbidity score. ConclusionsOne third of South Asian adults had higher metabolic comorbidity score. Physical inactivity, daily sedentary hours and minimal alcohol consumption was associated with higher metabolic comorbidity score.

Energy-Aware 3D Path Planning by Autonomous Ground Vehicle in Wireless Sensor Networks

Wireless sensor networks are used to monitor the environment, to detect anomalies or any other problems and risks in the system. If used in the transportation network, they can monitor traffic and detect traffic risks. In wireless sensor networks, energy constraints must be handled to enable continuous environmental monitoring and surveillance data gathering and communication. Energy-aware path planning of autonomous ground vehicle charging for sensor nodes can solve energy and battery replacement problems. This paper uses the Nearest Neighbour algorithm for the energy-aware path planning problem with an autonomous ground vehicle. Path planning simulations show that the Nearest Neighbour algorithm converges faster and produces a better solution than the genetic algorithm. We offer robust and energy-efficient path planning algorithms to swiftly collect sensor data with less energy, allowing the monitoring system to respond faster to anomalies. Positioning communicating sensors closer minimizes their energy usage and improves the network lifetime. This study also considers the scenario in which it is recommended to avoid taking direct travelling pathways between particular node pairs for a variety of different reasons. To address this more challenging scenario, we provide an Obstacle-Avoided Nearest Neighbour-based approach that has been adapted from the Nearest Neighbour approach. Within the context of this technique, the direct paths that connect the nodes are restricted. Even in this case, the Obstacle-Avoided Nearest Neighbour-based approach achieves almost the same performance as the the Neighbour-based approach.

Descriptive analysis of diseases, non-battle injuries and climate among deployed Swedish military personnel

IntroductionHistorically, diseases and non-battle injuries (DNBI) typically stand for 70%‒95% of all medical events during military missions. There is, however, no comprehensive compilation of medical statistics for Swedish soldiers during...

A procedure for surveillance data-driven risk assessment to inform Campylobacter risk-based control

In this study is presented a procedure for surveillance data-driven risk assessment, which can be used to inform inter-sectorial Campylobacter risk-based control, e.g. within National Action Plans and One Health (OH) systems. Campylobacter surveillance data (2019 to 2022) and a published quantitative microbial risk assessment (QMRA) model were used, to show the procedure. Moreover, an interface tool was developed in Excel for showing descriptive statistics on measured apparent flock prevalence (AP) and concentrations (colony forming units per gram, cfu/g) on the meat, together with their related QMRA outputs. Currently (mid-2024), Danish fresh broiler meat is produced by four slaughterhouse companies (A, B, C and D), where approximately 30 % of the annually slaughtered broiler flocks are randomly culture tested, on one leg skin (LS) sample per flock sampled from chilled carcasses. Data variables were: date of sampling, farm-ID, within farm house-ID, flock-ID, slaughterhouse name, sample-ID, and Campylobacter concentrations. Flocks were classified as carcass positive with a concentration ≥ 10 cfu/g. The data was fed into the QMRA model to assess: a) the average risk of human campylobacteriosis per serving (during a month or year), and b) the monthly/annual risk of 2022 relative (RR) to the baseline (average) risk from the previous three years. The descriptive statistics and the risk assessment (RA) were carried out at national level and for each slaughterhouse. In 2022, the national RR was 1.03, implying that the average annual risk increased by approximately 3 % compared to the baseline. Nevertheless, for slaughterhouses A, B and D, the annual risk decreased by ≈ 22 %, 21 % and 43 %, respectively; whereas for slaughterhouse C it increased by 48 %. Monthly risk estimates showed seasonal variations, according to the visualized changes of AP and meat contaminations. The national monthly RR was >1 in July and from September to December. During those months: slaughterhouse C had always RR > 1, slaughterhouse A had a relative increase of risk in July, slaughterhouse B in July and November, and slaughterhouse D in October and December. The procedure and the tools used in this study, allow identifying the impact of seasonality and food-chain stages (i.e. slaughterhouses and their broilers sourcing farms) on the risk per serving, so that Campylobacter risk-based control could be implemented accordingly, from farm to fork, across consecutive surveillance periods. The same principles could be applied in other countries, food chains, and/or for other foodborne pathogens, when similar data and QMRA models are available.

Predictors of HIV Care Outcomes among Recently Out-of-Care Individuals in The Massachusetts Cooperative Re-engagement Controlled Trial Cohort.

A cohort of individuals in care for HIV infection who were identified as being recently out-of-care (OOC) was recruited for a trial using a data-to-care approach and an intervention to facilitate re-engagement and retention in care. This allowed for analysis of demographic and clinical characteristics correlated with recently being OOC, re-engagement, and successful retention in care and viral suppression. Recently OOC persons with HIV infection (PWH) were identified for enrollment in the Cooperative Re-engagement Controlled Trial (CoRECT). CoRECT employed a data-to-care strategy, using both clinical and surveillance data, and an active public health re-engagement intervention. We estimated relative risks (RRs), unadjusted and with multivariate log binomial regression models, to analyze associations between sociodemographic and clinical predictors of being OOC, re-engagement, retention in care, and viral suppression. Of the 630 OOC PWH enrolled in CoRECT, most were male (72.7%) and over 30 years old (91.3%). Almost 40.0% were Black non-Hispanic, 29.7% were non-US born, and 41.6% were men who have sex with men (MSM). Possible predictors of re-engagement, retention in care, and viral suppression included younger age, Hispanic race/ethnicity, birth in a US dependency, AIDS status, and HIV exposure mode. Viral suppression status within 1-year pre-enrollment was significantly associated with all outcomes: re-engagement (aRR 1.28), retention (aRR 1.72), viral suppression (aRR 1.81), and durable viral suppression (aRR 3.30). Findings elucidate factors associated with care engagement and continuity for recently OOC PWH which can be used to inform targeted re-engagement activities for priority populations and guide future data-to-care interventions.

A dynamic ensemble model for short-term forecasting in pandemic situations.

During the COVID-19 pandemic, many hospitals reached their capacity limits and could no longer guarantee treatment of all patients. At the same time, governments endeavored to take sensible measures to stop the spread of the virus while at the same time trying to keep the economy afloat. Many models extrapolating confirmed cases and hospitalization rate over short periods of time have been proposed, including several ones coming from the field of machine learning. However, the highly dynamic nature of the pandemic with rapidly introduced interventions and new circulating variants imposed non-trivial challenges for the generalizability of such models. In the context of this paper, we propose the use of ensemble models, which are allowed to change in their composition or weighting of base models over time and could thus better adapt to highly dynamic pandemic or epidemic situations. In that regard, we also explored the use of secondary metadata-Google searches-to inform the ensemble model. We tested our approach using surveillance data from COVID-19, Influenza, and hospital syndromic surveillance of severe acute respiratory infections (SARI). In general, we found ensembles to be more robust than the individual models. Altogether we see our work as a contribution to enhance the preparedness for future pandemic situations.

The Global Measles and Rubella Laboratory Network Supports High-Quality Surveillance.

With 762 laboratories, the Global Measles and Rubella Laboratory Network (GMRLN) is the largest laboratory network coordinated by the World Health Organization (WHO). Like the Global Polio Laboratory Network, the GMRLN has multiple tiers, including global specialized laboratories, regional reference laboratories, national laboratories, and, in some countries, subnational laboratories. Regional networks are supervised by regional laboratory coordinators reporting to a global coordinator at WHO headquarters. Laboratories in the GMRLN have strong links to national disease control and vaccination programs. The GMRLN's goal is to support member states in obtaining timely, complete, and reliable laboratory-based surveillance data for measles and rubella as part of the strategy for achieving measles and rubella elimination. Surveillance data are reported to the national program and are included in annual reports on the status of measles and rubella elimination to national verification committees for review by regional verification commissions. Quality within the GMRLN is ensured by monitoring performance through external quality assurance programs, confirmatory and quality control testing, accreditation, and coordination of corrective action and training where needed. The overall performance of the laboratories has remained high over the years despite many challenges, particularly the COVID-19 pandemic. The GMRLN is well-positioned to support high-quality laboratory-based surveillance for measles and rubella and to transition to supporting laboratory testing for other pathogens, including vaccine-preventable diseases.

Evaluation of indications and efficacy of doxycycline for surgical antibiotic prophylaxis.

Given medical advancements in global healthcare systems over the past decade, it may be reasonable to assume that the incidence of surgical site infections would have decreased; however, surveillance data indicate that these rates have held constant. Surgical prophylaxis guidelines from the United States and United Kingdom recommend cefazolin, vancomycin and clindamycin in most surgeries for no longer than 24 hours. As a result of medication shortages impacting the global supply chain, surgeons have needed to evaluate alternative perioperative antibiotics, such as doxycycline; however, research into using doxycycline for preventing surgical site infections is limited. The goal of this study is to retrospectively assess doxycycline's efficacy, safety and role in preventing surgical site infections.