Electronic Surveillance System Research Articles

Associations between clinically diagnosed medical conditions and dietary supplement use: the US military dietary supplement use study.

This study examined associations between multiple dietary supplement (DS) categories and medical conditions diagnosed by health professionals. Cross-sectional. Volunteers completed an online questionnaire on DS use and demographic/lifestyle factors. Medical diagnoses were obtained from a comprehensive military electronic medical surveillance system and grouped into twenty-four clinically diagnosed medical conditions (CDMC). A stratified random sample of US service members (SM) from all military services (n 26 680). After adjustment for demographic/lifestyle factors (logistic regression), higher risk was found for 92 % (22/24) of CDMC among individual vitamins/minerals users, 58 % (14/24) of CDMC among herbal users, 50 % (12/24) of CDMC among any DS users and 46 % (11/24) of CDMC among multivitamins/multiminerals (MVM) users. Among protein/amino acid (AA) users, risk was lower in 25 % (6/24) of CDMC. For combination products, risk was higher in 13 % (3/24) of CDMC and lower in 8 % (2/24). The greater the number of CDMC, the higher the prevalence of DS use in most DS categories except proteins/AA where prevalence decreased. Users in many DS categories had a greater number of CDMC, but protein/AA users had fewer CDMC; results for combination products were mixed. These data indicate those with certain CDMC were also users in some DS categories, especially individual vitamins/minerals, herbals and MVM. Data are consistent with the perception that use of DS enhances health, especially in those with CDMC. Protein/AA and combination product users were more likely to be younger, more physically active men, factors that likely reduced CDMC.

Long Short-term Memory-Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation.

The potential to harness the plurality of available data in real time along with advanced data analytics for the accurate prediction of influenza-like illness (ILI) outbreaks has gained significant scientific interest. Different methodologies based on the use of machine learning techniques and traditional and alternative data sources, such as ILI surveillance reports, weather reports, search engine queries, and social media, have been explored with the ultimate goal of being used in the development of electronic surveillance systems that could complement existing monitoring resources. The scope of this study was to investigate for the first time the combined use of ILI surveillance data, weather data, and Twitter data along with deep learning techniques toward the development of prediction models able to nowcast and forecast weekly ILI cases. By assessing the predictive power of both traditional and alternative data sources on the use case of ILI, this study aimed to provide a novel approach for corroborating evidence and enhancing accuracy and reliability in the surveillance of infectious diseases. The model's input space consisted of information related to weekly ILI surveillance, web-based social (eg, Twitter) behavior, and weather conditions. For the design and development of the model, relevant data corresponding to the period of 2010 to 2019 and focusing on the Greek population and weather were collected. Long short-term memory (LSTM) neural networks were leveraged to efficiently handle the sequential and nonlinear nature of the multitude of collected data. The 3 data categories were first used separately for training 3 LSTM-based primary models. Subsequently, different transfer learning (TL) approaches were explored with the aim of creating various feature spaces combining the features extracted from the corresponding primary models' LSTM layers for the latter to feed a dense layer. The primary model that learned from weather data yielded better forecast accuracy (root mean square error [RMSE]=0.144; Pearson correlation coefficient [PCC]=0.801) than the model trained with ILI historical data (RMSE=0.159; PCC=0.794). The best performance was achieved by the TL-based model leveraging the combination of the 3 data categories (RMSE=0.128; PCC=0.822). The superiority of the TL-based model, which considers Twitter data, weather data, and ILI surveillance data, reflects the potential of alternative public sources to enhance accurate and reliable prediction of ILI spread. Despite its focus on the use case of Greece, the proposed approach can be generalized to other locations, populations, and social media platforms to support the surveillance of infectious diseases with the ultimate goal of reinforcing preparedness for future epidemics.

1204. Catheter-Associated Urinary Tract Infections (CAUTIs) and Secondary Hospital-Onset Bloodstream Infections (HO-BSIs)… Only the Tip of the Iceberg?

Abstract Background HO-BSIs – secondary to urinary tract infections (UTIs) – can result in substantial morbidity and mortality. The Centers for Disease Control and Prevention report that CAUTIs are the leading cause of secondary BSIs. However, more than 70% of hospital-onset UTIs (HO-UTIs) may be non-device associated. If that is the case, are a substantial number of HO-BSIs caused by non-CAUTI HO-UTIs? Methods A retrospective cohort analysis of nosocomial infections from 37 US hospitals was conducted using de-identified, real-world data from an electronic infection surveillance system. The analytic cohort included adults ≥ 18 years, without an infection diagnosis, and hospital length of stay ≥ 2 days, between October 2015 and June 2019. HO-UTI subjects presented with a non-contaminated positive urine culture on day 3 or later. Clinically meaningful HO-UTIs, were those with antimicrobials ordered ±2 days of the positive urine culture. CAUTI was defined per the National Healthcare Safety Network definition. Non-CAUTI HO-UTI were HO-UTIs not meeting the CAUTI definition. Secondary HO-BSIs were defined as non-contaminated, positive blood cultures occurring 2 days before or 4 days after the positive urine specimen, requiring an antimicrobial susceptibility test, and presenting with the same pathogen. Results Of the 568,293 inpatient admissions, 465,246 met the inclusion criteria. The vast majority of CAUTIs (401 of 436; 92%) and 75% of non-CAUTI HO-UTIs (3,256 of 4,374) were clinically meaningful. The relative burden of secondary HO-BSI was greater in patients with CAUTI (8%) compared to non-CAUTI HO-UTI (3%). However, the absolute risk of secondary HO-BSI was 3-times greater in non-CAUTI HO-UTI compared to CAUTI (96 cases vs 32 cases, respectively). 56% of secondary HO-BSI in CAUTI, and only 31% of secondary HO-BSI in non-CAUTI HO-UTI, likely originated in the intensive care unit (ICU). Case Tree Frequency of CAUTI and non-CAUTI HO-UTI. Frequency of secondary HO-BSI. Location of HO-UTI. Conclusion This retrospective, observational study found clinically meaningful non-CAUTI HO-UTIs to be 10-fold higher than the number of CAUTIs. In addition, the absolute burden of secondary HO-BSI is substantially higher in these non-CAUTI HO-UTIs and more likely to be associated with the non-ICU setting. The data suggests that evaluating CAUTI alone may underestimate the true burden of clinically meaningful HO-UTI. Disclosures ChinEn Ai, MPH, BD - Becton, Dickinson and Company: Employee|BD - Becton, Dickinson and Company: Stocks/Bonds Molly Jung, MPH, BD - Becton, Dickinson and Company: Employee|BD - Becton, Dickinson and Company: Stocks/Bonds Timothy Kelly, MS, MBA, BD - Becton, Dickinson and Company: Employee|BD - Becton, Dickinson and Company: Stocks/Bonds Kalvin Yu, MD, FIDSA, Becton, Dickinson and Company: Employee of, and shareholder in, Becton, Dickinson and Company, and the company received funding from GlaxoSmithKline plc. to conduct this study|GlaxoSmithKline plc.: GlaxoSmithKline plc.-sponsored study 212502.

Short sleep duration is associated with a wide variety of medical conditions among United States military service members

ObjectivesThis cross-sectional study investigated self-reported sleep duration and its association with a comprehensive range of clinically-diagnosed medical condition categories (CDMCs), as well as the relationship between short sleep duration (≤6 h) and demographic/lifestyle factors, among United States military service members (SMs). MethodsA stratified random sample of SMs (n = 20,819) completed an online questionnaire on usual daily hours of sleep and demographic/lifestyle characteristics. CDMCs for a six-month period prior to questionnaire completion were obtained from a comprehensive military electronic medical surveillance system and grouped into 33 CDMCs covering both broad and specific medical conditions. Prevalence of CDMCs was compared among three sleep duration categories (≤4, 5–6 and ≥7 h). ResultsSMs reported a mean ± standard deviation of 6.3 ± 1.4 h of sleep per day. After adjustment for demographic/lifestyle characteristics, shorter sleep duration was associated with higher odds of a medical condition in 25 of 33 CDMCs, with most (n = 20) demonstrating a dose-response relationship. The five CDMCs with the largest differences between ≤4 vs ≥ 7 h sleep were: diseases of the nervous system (odds ratio [OR] = 2.9, 95% confidence interval [95%CI] = 2.4–3.4), mental/behavioral diseases (OR = 2.7, 95%CI = 2.3–3.2), diseases of the musculoskeletal system (OR = 1.9, 95%CI = 1.6–2.1), diseases of the circulatory system (OR = 1.7, 95%CI = 1.3–2.2), and diseases of the digestive system (OR = 1.6, 95%CI = 1.2–2.0). Six hours of sleep or less was independently associated with older age, less formal education, race, Hispanic ethnicity, higher body mass index, smoking, and military service branch. ConclusionsIn this young, physically active population, reporting shorter sleep duration was associated with a higher risk of multiple CDMCs.

Hepatitis B in Poland in 2020.

Aim of the study was the assessment of hepatitis B epidemiological situation in Poland in 2019 compared to previous years, taking into consideration the impact of the COVID-19 pandemic during that time. Data for 2020 included in individual reports on hepatitis B and HBV infections recorded by sanitary and epidemiological stations at EpiBaza, i.e. in the electronic epidemiological surveillance system on infectious diseases, were analyzed. In the assessment of the epidemiological situation, data published in the annual bulletins: "Infectious diseases and poisonings in Poland in 2020" and "Vaccinations in Poland in 2020" were also used. Data on deaths were obtained from the Statistics Poland (GUS). In 2020, 2,854 cases of hepatitis B were reported, which corresponds to the incidence of 2.59 per 100,000 population, lower by 65.1% than in 2019. 14 cases of acute hepatitis B were reported, constituting 1.4% of all registered cases. The incidence of acute hepatitis B was 0.04 per 100,000 population and was lower by 67% compared to 2019 and lower by 71% compared to the median for the years 2014-2018. There were no cases of acute disease in the age group 0-29 years. A total of 978 chronic and unknown hepatitis B cases (UNK) were registered and the diagnosis rate was 2.56 per 100,000 population, lower by 64.2% than in 2019. Compared to the median diagnosis rate of chronic hepatitis B in 2014-2018, a decrease of 70.4% was observed. In the age group 0-19 years, there was no case reported. In 2020, 24 people died due to hepatitis B, including 22 from chronic hepatitis B. The COVID-19 pandemic resulted in a significant reduction in the number of HBV tests performed and, consequently, a reduction in the number of diagnosed infections. A decrease in the number of detected infections was observed from the second quarter of 2020, i.e. from the beginning of the COVID-19 pandemic, although already in the first quarter of 2020 the number of registered hepatitis B cases was lower than in the same period in 2019. No acute cases were reported among people who were vaccinated against hepatitis B during childhood. Vaccination with three doses of hepatitis B vaccine in children in the second year of life was only slightly lower than in 2019, which proves the stability of the implementation of the preventive vaccination program, despite the limited access to primary health care during the pandemic.

Big Geospatial Data and Data-Driven Methods for Urban Dengue Risk Forecasting: A Review

With advancements in big geospatial data and artificial intelligence, multi-source data and diverse data-driven methods have become common in dengue risk prediction. Understanding the current state of data and models in dengue risk prediction enables the implementation of efficient and accurate prediction in the future. Focusing on predictors, data sources, spatial and temporal scales, data-driven methods, and model evaluation, we performed a literature review based on 53 journal and conference papers published from 2018 to the present and concluded the following. (1) The predominant predictors include local climate conditions, historical dengue cases, vegetation indices, human mobility, population, internet search indices, social media indices, landscape, time index, and extreme weather events. (2) They are mainly derived from the official meteorological agency satellite-based datasets, public websites, department of health services and national electronic diseases surveillance systems, official statistics, and public transport datasets. (3) Country-level, province/state-level, city-level, district-level, and neighborhood-level are used as spatial scales, and the city-level scale received the most attention. The temporal scales include yearly, monthly, weekly, and daily, and both monthly and weekly are the most popular options. (4) Most studies define dengue risk forecasting as a regression task, and a few studies define it as a classification task. Data-driven methods can be categorized into single models, ensemble learning, and hybrid learning, with single models being further subdivided into time series, machine learning, and deep learning models. (5) Model evaluation concentrates primarily on the quantification of the difference/correlation between time-series observations and predicted values, the ability of models to determine whether a dengue outbreak occurs or not, and model uncertainty. Finally, we highlighted the importance of big geospatial data, data cloud computing, and other deep learning models in future dengue risk forecasting.

Rapid Increase in Suspected SARS-CoV-2 Reinfections, Clark County, Nevada, USA, December 2021.

Genetic differences between SARS-CoV-2 variants raise concerns about reinfection. Public health authorities monitored the incidence of suspected reinfection in Clark County, Nevada, USA, during March 2020–March 2022. Suspected reinfections, defined as a second positive PCR test collected >90 days after an initial positive test, were monitored through an electronic disease surveillance system. We calculated the proportion of all new cases per week that were suspected reinfections and rates per 1,000 previously infected persons by demographic groups. The rate of suspected reinfection remained <2.7% until December 2021, then increased to ≈11%, corresponding with local Omicron variant detection. Reinfection rates were higher among adults 18–50 years of age, women, and minority groups, especially persons identifying as American Indian/Alaska Native. Suspected reinfection became more common in Clark County after introduction of the Omicron variant, and some demographic groups are disproportionately affected. Public health surveillance could clarify the SARS-CoV-2 reinfection burden in communities.

Surface Tensions: Skate-Stoppers and the Surveillance Politics of Small Spaces

Skate-stoppers are ubiquitous objects installed on outdoor surfaces in built environments all over the world. Skate-stoppers are an essential part of low-tech security of urban surfaces at a micro-scale—a single bench, handrail, or ledge—with the sole-purpose of protecting these surfaces from skateboarders. As such skate-stoppers are an extension of human and electronic surveillance systems, though in many patches of the urban landscape, skate-stoppers are a low-cost substitute for more sophisticated technologies. This interplay of control and liberation draws attention to surfaces in urban space and specific tactics adopted to secure and protect them through surveillance. In this article, we explore the criticality of skate-stoppers and tactics for removing them to advance the study of surveillance of small spaces. We argue that skate-stoppers are aggressive attempts to control urban space by interrupting the flow of bodies and boards along particular surfaces, namely the “spots” desired by skateboarders. Second, we argue that the installation of skate-stoppers has shifted from reaction to anticipation of skateboarders, and new construction projects now come with skate-stoppers already installed as part of surveillance infrastructure. Third, we argue that skateboarders have become adept at liberating spots from skate-stoppers, restoring flow to surfaces through both organised activism and covert acts, underscoring the limitations of surveillance using objects. We conclude with some thoughts on the disjuncture between the embrace of creative cities and the proliferation of skate-stoppers, suggesting creative play and its desired affective properties are regulated by the control of surfaces in the same spaces.

Piloting an Electronic Sepsis Alerting System to Reduce Inpatient Sepsis-related Serious Safety Events.

Background: Electronic surveillance systems that enable continuous patient screening for emerging signs of sepsis may improve sepsis recognition and patient outcomes. Objectives: An electronic sepsis alerting system was piloted on Pediatric Medicine units at a tertiary care hospital. The pilot served to refine the system and accompanying workflow before hospital-wide implementation, aiming to reduce inpatient serious safety events related to delayed sepsis recognition. Methods: The multitiered intervention included (1) an electronic sepsis screening and alerting system; (2) an interdisciplinary huddle workflow; (3) risk stratification nomenclature (continue routine care, sepsis watch, code sepsis) to reconcile alerts; and (4) streamlined documentation and ordering tools. Iterative changes were made to the tools and workflow using plan, do, study, act cycle methodology. Measures of clinician adherence to the workflow were tracked monthly during the pilot (% alerts reconciled, % alerts with documented huddle note). Alert to huddle time and huddle to reconciliation time (target: 10 minutes) served as outcome measures for the pilot. The frequency of consults to the hospital’s critical care response team for the indication of query sepsis was monitored as a balancing measure. Alert frequency, rate of corresponding clinical concern for sepsis, and missed sepsis cases were tracked as measures of screening tool utility. Results: During the 3-month pilot, 86% of alerts were reconciled and 67% had a documented huddle note. The median alert to huddle time decreased from 9 to 3 minutes over the course of the pilot. The median huddle to reconciliation time decreased from 14 to 8 minutes. The frequency of CCRT consults during the pilot was 1 per month, which was increased slightly from the baseline frequency of 0.67 consults per month over the previous year. An alert was triggered for 4.1% of opportunities (average 2.2 alerts per day). Of the alerts reconciled, 29% indicated a concern for sepsis. There were four instances of clinical concern for sepsis where no alert was triggered. The sepsis huddle workflow was followed in three of these instances. Conclusions/implications: Pilot results suggest clinician adherence to a new streamlined approach to care for inpatients at risk for sepsis. Involving clinicians in system design and embedding electronic tools within existing care processes supported workflow uptake. Future efforts will focus on optimizing the alerting system’s clinical accuracy and examining its impact on clinical outcomes.

Parents' experiences and perceptions of the acceptability of a whole-hospital, pro-active electronic pediatric early warning system (the DETECT study): A qualitative interview study.

BackgroundFailure to recognize and respond to clinical deterioration in a timely and effective manner is an urgent safety concern, driving the need for early identification systems to be embedded in the care of children in hospital. Pediatric early warning systems (PEWS) or PEW scores alert health professionals (HPs) to signs of deterioration, trigger a review and escalate care as needed. PEW scoring allows HPs to record a child’s vital signs and other key data including parent concern.AimThis study aimed to explore the experiences and perceptions of parents about the acceptability of a newly implemented electronic surveillance system (the DETECT surveillance system), and factors that influenced acceptability and their awareness around signs of clinical deterioration and raising concern.MethodsDescriptive, qualitative semi-structured telephone interviews were undertaken with parents of children who had experienced a critical deterioration event (CDE) (n = 19) and parents of those who had not experienced a CDE (non-CDE parents) (n = 17). Data were collected between February 2020 and February 2021.ResultsQualitative data were analyzed using generic thematic analysis. Analysis revealed an overarching theme of trust as a key factor that underpinned all aspects of children’s vital signs being recorded and monitored. The main themes reflect three domains of parents’ trust: trust in themselves, trust in the HPs, and trust in the technology.ConclusionParents’ experiences and perceptions of the acceptability of a whole-hospital, pro-active electronic pediatric early warning system (The DETECT system) were positive; they found it acceptable and welcomed the use of new technology to support the care of their child.

A near real-time electronic health record-based COVID-19 surveillance system: An experience from a developing country.

ContextAccess to real-time data that provide accurate and timely information about the status and extent of disease spread could assist management of the COVID-19 pandemic and inform decision-making.AimTo demonstrate our experience with regard to implementation of technical and architectural infrastructure for a near real-time electronic health record-based surveillance system for COVID-19 in Iran.MethodThis COVID-19 surveillance system was developed from hospital information and electronic health record (EHR) systems available in the study hospitals in conjunction with a set of open-source solutions; and designed to integrate data from multiple resources to provide near real-time access to COVID-19 patients’ data, as well as a pool of health data for analytical and decision-making purposes.OutcomesUsing this surveillance system, we were able to monitor confirmed and suspected cases of COVID-19 in our population and to automatically notify stakeholders. Based on aggregated data collected, this surveillance system was able to facilitate many activities, such as resource allocation for hospitals, including managing bed allocations, providing and distributing equipment and funding, and setting up isolation centres.ConclusionElectronic health record systems and an integrated data analytics infrastructure are effective tools to enable policymakers to make better decisions, and for epidemiologists to conduct improved analyses regarding COVID-19.ImplicationsImproved quality of clinical coding for better case finding, improved quality of health information in data sources, data-sharing agreements, and increased EHR coverage in the population can empower EHR-based COVID-19 surveillance systems.

Factors contributing to the high prevalence of multidrug-resistance/Rifampicin-resistance in patients with tuberculosis: an epidemiological cross sectional and qualitative study from Khabarovsk krai region of Russia

BackgroundGrowing prevalence of multidrug-resistant/Rifampicin-resistant tuberculosis (MDR/RR-TB; resistance to Isoniazid and Rifampicin/Isolated resistance to Rifampicin) is putting in jeopardy the WHO End TB strategy. This study aimed to identify factors contributing to the high prevalence of MDR/RR-TB in Khabarovsk krai region of Russia.MethodsA cross-sectional retrospective study was conducted, analyzing clinical, demographic, and drug susceptibility testing data on 1440 patients. As a source of raw data, the national electronic TB surveillance system was used. Anonymous data was collected on every patient diagnosed with TB in all healthcare facilities of the region from January 2018 to December 2019. Only patients with proven excretion of m. tuberculosis were included in the study. Factors associated with MDR/RR-TB were identified through logistic regression analysis, in conjunction with in-depth interviews with eight patients, five healthcare managers and five doctors.Findings2661 patients were identified with TB, 1440 were incorporated in the study based on inclusion criteria. Of these, 618 (42.9%) were identified with MDR/RR-TB. Patients with a history of imprisonment were 16.53 times (95% CI 5.37 to 50.88,) more likely to have MDR/RR-TB, whereas re-treatment patients were 2.82 times (95% CI 2.16 to 3.66) more likely to have MDR/RR-TB. Other influencing factors included presence of disability (AOR is 2.32, 95% CI 1.38 to 3.89), cavitary disease (AOR is 1.76, 95% CI 1.37 to 2.25), and retirement status (AOR 0.65, 95% CI 0.43 to 0.98, p = 0.042). Poor patient knowledge and understanding of the disease, progressive weariness of prolonged TB treatment, and inability hospitalize infectious patients without their consent were perceived by the interviewees as major influencing factors.ConclusionsIncarceration and treatment history, regardless of outcome, were identified as major factors influencing MDR/RR-TB prevalence. It is essential for the TB care system to eliminate legal loopholes, which deprive doctors of means to enforce quarantine procedures and epidemiological surveillance on infected patients, former and current inmates. Increasing people’s awareness of TB, early detection and appropriate treatment of patients with TB are needed for successfully combating MDR/RR-TB.

Creation of a Novel Approach to Surveillance Through a Consolidated Abstraction Service

<h3>Background</h3> Abstraction for surveillance purposes is time consuming and can interrupt other duties required of infection preventionists (IP). While contracted services exist, they come at a cost and provide little ancillary value to an organization. Thus, we chose to create a consolidated abstraction service within our healthcare system with the goal of ensuring quality data through standardized application of National Healthcare Safety Network (NHSN) definitions and reducing variance through improved connection and collaboration. <h3>Methods</h3> The Clinical Data Registry Abstraction (CDRA) program was initiated in January 2020 as a shared service model, with 29 level 1 abstractors and 44 level 2 abstractors, plus a leadership team. Skill levels varied from no experience to extensive experience and Certified Infection Control (CIC) certification. The program included an intensive 8-week training program, monthly education seminars, and validation reviews with feedback for improvement. Communications channels were established for sharing best practices. The program covers 185 acute care facilities associated other sites of care across the United States. Abstractors use an electronic surveillance system to review daily cultures and complete an infection document that is sent to the IP for final review prior to submission to NHSN. <h3>Results</h3> A survey (59% facility response rate) rated the program 4.13 out of 5 overall. The domains of responsiveness and knowledge base were rated high, and 81% of respondents indicated that they received 1 to 3 hours back in their day. Survey comments highlighted IP retention, increased collaboration, return on investment for facilities, and reduction of IP workload as benefits. Areas for improvement included improving timeliness, expanding the scope, further standardization of processes, and increasing opportunities for shared learning. <h3>Conclusions</h3> In total, the CDRA program is a successful consolidated abstraction service that adds value to facilities and the organization. Investment in similar programs provides a valid alternative to contracted abstraction services.

Continuous surveillance of drug-resistant TB burden in Rwanda: a retrospective cross-sectional study.

Since the roll-out of the Xpert MTB/RIF assay, continuous surveillance can provide an estimate of rifampicin-resistant TB (RR-TB) prevalence, provided high drug susceptibility testing (DST) coverage is achieved. We use national data from Rwanda to describe rifampicin DST coverage, estimate the prevalence of RR-TB and assess its predictors. Routinely collected DST data were entered into an electronic TB case-based surveillance system. DST coverage was calculated among all bacteriologically confirmed pulmonary TB patients notified from 1 July 2019 to 30 June 2020 in Rwanda. The prevalence of RR-TB was estimated among those with DST results. Univariable and multivariable analysis was performed to explore predictors for RR TB. Among 4066 patients with bacteriologically confirmed pulmonary TB, rifampicin DST coverage was 95.6% (4066/4251). RR-TB was diagnosed in 73 patients. The prevalence of RR-TB was 1.4% (53/3659; 95% CI 1.09 to 1.89%) and 4.9% (20/406; 95% CI 3.03 to 7.51%) in new and previously treated TB cases, respectively. Predictors of RR-TB were: (1) living in Kigali City (adjusted OR [aOR] 1.65, 95% CI 1.03 to 2.65); (2) previous TB treatment (aOR 3.64, 95% CI 2.14 to 6.19); and (3) close contact with a known RR-TB patient (aOR 11.37, 95% CI 4.19 to 30.82). High rifampicin DST coverage for routine reporting allowed Rwanda to estimate the RR-TB prevalence among new and previously treated patients.

Vigilancia epidemiológica en pandemia de COVID-19: Sistema EPIVIGILA

In March 2020, the first version of EPIVIGILA was deployed in a productive environment a few days after the first local case of COVID- 19. This system is a technological integration plat-form for national epidemiological surveillance of notifiable diseases. Previously, Chile used a manual process that would probably have failed with a peak volume of more than 38 000 daily notifications; in a country with 18 million inhabitants, long and narrow geography, and centralized governance. This work highlights the importance of the national electronic surveillance system – EPIVIGILA – in managing the pandemic. The system’s main strength is its ability to adapt to the needs of reliable, precise, timely, and real- time information. EPIVIGILA was able to include, under the circumstances, different flows, actors, data, and functionalities with high expectations of accuracy. This valuable information allowed the authorities to assess the impact of the measures to manage and control the pandemic. Its versatility positions this platform among the few globally that operates national data with a high level of granularity in a single system through a pandemic. In Chile, EPIVIGILA is the primary source of information for daily reports, epidemiological reports, and data published on government websites about COVID- 19. Thus, electronic systems prove fundamental for public health because the recording and processing of data generate clear, reliable, and timely information, helping authorities make decisions to reduce the spread of infectious diseases, prevent deaths, and improve the population’s quality of life.

Epidemiological surveillance in COVID- 19 pandemic: EPIVIGILA system.

In March 2020, the first version of EPIVIGILA was deployed in a productive environment a few days after the first local case of COVID- 19. This system is a technological integration plat-form for national epidemiological surveillance of notifiable diseases. Previously, Chile used a manual process that would probably have failed with a peak volume of more than 38 000 daily notifications; in a country with 18 million inhabitants, long and narrow geography, and centralized governance. This work highlights the importance of the national electronic surveillance system EPIVIGILA in managing the pandemic. The systems main strength is its ability to adapt to the needs of reliable, precise, timely, and real- time information. EPIVIGILA was able to include, under the circumstances, different flows, actors, data, and functionalities with high expectations of accuracy. This valuable information allowed the authorities to assess the impact of the measures to manage and control the pandemic. Its versatility positions this platform among the few globally that operates national data with a high level of granularity in a single system through a pandemic. In Chile, EPIVIGILA is the primary source of information for daily reports, epidemiological reports, and data published on government websites about COVID- 19. Thus, electronic systems prove fundamental for public health because the recording and processing of data generate clear, reliable, and timely information, helping authorities make decisions to reduce the spread of infectious diseases, prevent deaths, and improve the populations quality of life.

Spatial analysis of tuberculosis treatment outcomes in Shanghai: implications for tuberculosis control.

Tuberculosis (TB) treatment outcomes are a key indicator in the assessment of TB control programs. We aimed to identify spatial factors associated with TB treatment outcomes, and to provide additional insights into TB control from a geographical perspective. We collected data from the electronic TB surveillance system in Shanghai, China and included pulmonary TB patients registered from January 1, 2009 to December 31, 2016. We examined the associations of physical accessibility to hospitals, an autoregression term, and random hospital effects with treatment outcomes in logistic regression models after adjusting for demographic, clinical, and treatment factors. Of the 53,475 pulmonary TB patients, 49,002 (91.6%) had successful treatment outcomes. The success rate increased from 89.3% in 2009 to 94.4% in 2016. The successful treatment outcome rate varied among hospitals from 78.6% to 97.8%, and there were 12 spatial clusters of poor treatment outcomes during the 8-year study period. The best-fit model incorporated spatial factors. Both the random hospital effects and autoregression terms had significant impacts on TB treatment outcomes, ranking 6th and 10th, respectively, in terms of statistical importance among 14 factors. The number of bus stations around the home was the least important variable in the model. Spatial autocorrelation and hospital effects were associated with TB treatment outcomes in Shanghai. In highly-integrated cities like Shanghai, physical accessibility was not related to treatment outcomes. Governments need to pay more attention to the mobility of patients and different success rates of treatment among hospitals.

Divergences between healthcare-associated infection administrative data and active surveillance data in Canada.

Although Canada has both a national active surveillance system and administrative data for the passive surveillance of healthcare-associated infections (HAI), both have identified strengths and weaknesses in their data collection and reporting. Active and passive surveillance work independently, resulting in results that diverge at times. To understand the divergences between administrative health data and active surveillance data, a scoping review was performed. Medline, Embase and Cumulative Index to Nursing and Allied Health Literature along with grey literature were searched for studies in English and French that evaluated the use of administrative data, alone or in comparison with traditional surveillance, in Canada between 1995 and November 2, 2020. After extracting relevant information from selected articles, a descriptive summary of findings was provided with suggestions for the improvement of surveillance systems to optimize the overall data quality. Sixteen articles met the inclusion criteria, including twelve observational studies and four systematic reviews. Studies showed that using a single source of administrative data was not accurate for HAI surveillance when compared with traditional active surveillance; however, combining different sources of data or combining administrative with active surveillance data improved accuracy. Electronic surveillance systems can also enhance surveillance by improving the ability to detect potential HAIs. Although active surveillance of HAIs produced the most accurate results and remains the gold-standard, the integration between active and passive surveillance data can be optimized. Administrative data can be used to enhance traditional active surveillance. Future studies are needed to evaluate the feasibility and benefits of potential solutions presented for the use of administrative data for HAI surveillance and reporting in Canada.

Clinical characteristics and microbiology of nosocomial enterococcal bloodstream infections in a tertiary-level hospital: a retrospective study, 2007–2019

Enterococci are important pathogens causing nosocomial bloodstream infections (BSIs) and cannot be treated with appropriate timely empirical antibiotics due to their natural resistance to many kinds of antibiotics. To analyse the clinical characteristics and microbiological features of nosocomial bloodstream infections caused by enterococci. The clinical characteristics and microbiological features of nosocomial enterococcal BSI patients in Xiamen University Zhongshan Hospital were examined in a case-controlled retrospective study. All patient information was collected through an electronic surveillance system. A total of 199 cases were identified as nosocomial enterococcal BSIs over a period of 13 years. The incidence of BSIs fluctuated from 0.21% to 0.81%. In the distribution of wards, enterococcal BSIs in hepatobiliary surgery ranked first. Intra-abdominal diseases (odds ratio: 3.36; 95% confidence interval: 2.15-5.27; P < 0.001), chemotherapy history (4.37; 2.06-9.25; P < 0.001), and urinary catheterization (2.34; 1.52-3.61; P < 0.001) were risk factors for nosocomial enterococcal BSI acquisition. Vancomycin-resistant enterococci and linezolid-insensitive enterococci strains were not found. Patients with a history of intra-abdominal disease, chemotherapy and urinary catheterization are at higher risk of nosocomial enterococcal bloodstream infections. The enterococcus strains were still sensitive to commonly used antibiotics.

Assessment of electronic surveillance and knowledge, attitudes, and practice (KAP) survey toward imported malaria surveillance system acceptance in France.

ObjectiveAn electronic surveillance system was released to monitor morbidity and mortality incidence of imported malaria cases, investigate autochthonous cases, and assess chemosensitivity of Plasmodium isolates among travelers to and from endemic areas. The aim of this study is to evaluate the use of an electronic surveillance system for imported malaria in France.Materials and MethodsThree main indicators were used to assess the online malaria web-based surveillance system: (1) the quality of the surveillance system; (2) the capacity of the online system to early warning in case of particular events of public health; (3) the knowledge, attitude, and practice of online electronic system by practitioners of malaria network in France.ResultsOverall, the median time onset a case is reported to the system decrease by 99%, ranging from 227 days (144–309) to 2 days (1–6) in 2006 and 2020, respectively.ConclusionThe online malaria surveillance system in France has demonstrated its effectiveness and can therefore be extended to carry out numerous investigations linked to research on malaria.