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1.
Lancet Digital Health ; 4(8):E573-E583, 2022.
Article in English | Web of Science | ID: covidwho-2092794

ABSTRACT

Background Real-time prediction is key to prevention and control of infections associated with health-care settings. Contacts enable spread of many infections, yet most risk prediction frameworks fail to account for their dynamics. We developed, tested, and internationally validated a real-time machine-learning framework, incorporating dynamic patient-contact networks to predict hospital-onset COVID-19 infections (HOCIs) at the individual level. Methods We report an international retrospective cohort study of our framework, which extracted patient-contact networks from routine hospital data and combined network-derived variables with clinical and contextual information to predict individual infection risk. We trained and tested the framework on HOCIs using the data from 51 157 hospital inpatients admitted to a UK National Health Service hospital group (Imperial College Healthcare NHS Trust) between April 1, 2020, and April 1, 2021, intersecting the first two COVID-19 surges. We validated the framework using data from a Swiss hospital group (Department of Rehabilitation, Geneva University Hospitals) during a COVID-19 surge (from March 1 to May 31, 2020;40 057 inpatients) and from the same UK group after COVID-19 surges (from April 2 to Aug 13, 2021;43 375 inpatients). All inpatients with a bed allocation during the study periods were included in the computation of network-derived and contextual variables. In predicting patient-level HOCI risk, only inpatients spending 3 or more days in hospital during the study period were examined for HOCI acquisition risk. Findings The framework was highly predictive across test data with all variable types (area under the curve [AUC]-receiver operating characteristic curve [ROC] 0.89 [95% CI 0.88-0.90]) and similarly predictive using only contact-network variables (0.88 [0.86-0.90]). Prediction was reduced when using only hospital contextual (AUC-ROC 0.82 [95% CI 0.80-0.84]) or patient clinical (0.64 [0.62-0.66]) variables. A model with only three variables (ie, network closeness, direct contacts with infectious patients [network derived], and hospital COVID-19 prevalence [hospital contextual]) achieved AUC-ROC 0.85 (95% CI 0.82-0.88). Incorporating contact-network variables improved performance across both validation datasets (AUC-ROC in the Geneva dataset increased from 0.84 [95% CI 0.82-0.86] to 0.88 [0.86-0.90];AUC-ROC in the UK post-surge dataset increased from 0.49 [0.46-0.52] to 0.68 [0.64-0.70]). Interpretation Dynamic contact networks are robust predictors of individual patient risk of HOCIs. Their integration in clinical care could enhance individualised infection prevention and early diagnosis of COVID-19 and other nosocomial infections. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

2.
BJU International ; 129:107, 2022.
Article in English | EMBASE | ID: covidwho-1956724

ABSTRACT

Introduction & Objectives: The significant reduction in elective surgery initially outlined by the National Cabinet in March 2020 and instituted by respective state governments due to the COVID-19 pandemic, led to a parallel overall reduction in patient based surgical training opportunities for trainees. The physical patient, as a training resource, was in short supply. In order to achieve competency and proficiency, surgical training in Australia and New Zealand is structured around each of the ten Royal Australasian College of Surgeons (RACS) competencies and occurs predominantly in a patient based clinical setting. Our objective was to quantify the impact of COVID-19 on surgical training, to appraise the establishment of our local regional hospital provision of urology service plan and assess the impact COVID-19 had on unit workload. We review the adaptive approach to surgical training taken up in our institution and highlight the unique challenges trainees were faced with due to the pandemic, allowing them to demonstrate many of the RACS nontechnical skill competencies Methods: To quantify the impact of COVID-19 on surgical training, we completed a retrospective audit of the Urology Department activity during each Victorian pandemic wave in 2020 at our large regional teaching hospital. Corresponding weeks in the year prior were used as the control. Interviews with department members illustrated the adaptive approach to surgical training used at our institution. Results: A State of Disaster Surgical Triage Team (SODSTT) was established with surgical operations split between one public and two private hospitals in our region. A pandemic triaging protocol was established, and 335 Category-2 patients were re-triaged. All meetings were moved to online video conferencing formats. The first wave saw a 13.8% reduction in clinic reviews, with the second wave having an overall increase of 8.8% with 56% being telehealth. The second wave saw an 11.0% reduction in overall operating, with reduced emergency operating in both the first and second wave of 17.4% and 45.5% respectively. These reductions impacted surgical technical skill training, resulting in surgical education provided through technology platforms including webinars, podcasts and pre-recorded operative videos. The unique challenges trainees were faced with due to the pandemic encouraged development and expertise of the non-technical RACS competencies. Conclusions: We must reflect on the continual changes in our departments, considering the use of all educational opportunities and tools to ensure our trainees continue to develop and progress through their training, with particular focus on RACS competencies and non-technical skills.

3.
Australian and New Zealand Journal of Psychiatry ; 56(SUPPL 1):214, 2022.
Article in English | EMBASE | ID: covidwho-1916675

ABSTRACT

Background: Symptoms after acute infection with COVID-19 can persist for weeks or months. Potential mechanisms include cell injury due to the virus, the consequences of the immunological response, abnormal clotting, medical comorbidity and secondary psychiatric disorders. Clinical experience and early research suggest some clustering of symptoms into differing syndromes. Multidisciplinary clinics established in tertiary hospitals have provided an opportunity to work with patients experiencing persisting symptoms and build an understanding as to their challenges and needs. Objectives: To (1) review the current knowledge regarding persistent symptoms after COVID-19;(2) provide a clinical perspective on the assessment and management of patients with persistent symptoms after COVID-19;and (3) identify potential developments in health care that may be required to address the need of patients with persistent symptoms after COVID-19. Methods: The presenters will summarise key learnings from their work in multidisciplinary COVID-19 hospital clinics in Sydney and Melbourne. Findings: Persistent symptoms after COVID-19 are common, but usually resolve over time. The mechanism for persistent symptoms is not fully understood and likely differs between patients. Conclusion: The MH practitioner's role in the management of persistent symptoms after COVID-19 includes, but is not limited to, the identification and management of secondary mental disorders and resisting the premature allocation of psychological mechanisms to somatic symptoms.

4.
Policy Brief - Tegemeo Institute of Agricultural Policy and Development 2021. (35):6 pp. ; 2021.
Article in English | CAB Abstracts | ID: covidwho-1897543

ABSTRACT

This policy brief summarizes a report which applies a systematic literature review methodology to survey the evidence on the impacts of the COVID-19 pandemic on sub-Saharan African food systems, particularly with respect to domestic food value chains, regional/international food trade, and food and nutrition security. This evidence synthesis gives rise to several recommendations for policy makers, some of which are immediately applicable while others would be relevant if a lockdown were reintroduced in a future crisis.

5.
Bju International ; 129:107-107, 2022.
Article in English | Web of Science | ID: covidwho-1894005
6.
Australian and New Zealand Journal of Psychiatry ; 56(1_SUPPL):214-214, 2022.
Article in English | Web of Science | ID: covidwho-1866166
7.
Annals of Emergency Medicine ; 78(4):S120, 2021.
Article in English | EMBASE | ID: covidwho-1748244

ABSTRACT

Study Objectives: At the peak of the initial COVID-19 outbreak in Italy, providers were required to make decisions related to resource rationing due to a shortage of medical equipment. Identifying COVID-19 positive patients who were high-risk for severe illness early in their course could have assisted in determining the most appropriate medical management in many cases. Currently, few models exist to predict the outcome of COVID-19 positive patients. Among those that do, none to our knowledge utilize Bayesian logistic regression. The goal of this study was to generate a model that would dynamically estimate the probability of severe disease in patients who test positive for COVID-19 during their initial emergency department (ED) visit. Methods: This model initially utilized a Bayesian approach with prior data based on the literature at the time, and after one week employed logistical regression using retrospective data from our own patient set. In total, data from 428 RT-PCR-confirmed COVID-19 patients who presented between March 4th and May 7th of 2020 was incorporated. Priors included: female sex, O2 Saturation, lymphocytes, LDH, and CRP. Data acquired during the patients’ encounter included co-morbidities, temperature, MAP, HR, ferritin, d-dimer, hs-troponin, platelets, total bilirubin, hgb, lactate, albumin, and SOFA score. Single imputation was utilized to address patients with missing data points. Our primary outcomes were vasopressor requirement, intubation, and death. Results: Utilizing these data points, a risk calculator for vasopressor requirement, intubation, and/or death was developed with a C-statistic of 0.85. See the supplementary materials for a comprehensive list of the regression coefficients, their betas, and standardized betas (Table 1) and a graph of our predicted primary outcomes compared to actual primary outcomes (Figure 1). Conclusion: A model predictive of vasopressor use, intubation, and death in COVID-19 positive patients was derived. By initially incorporating Bayesian logistic regression and prior data, this model could have theoretically been utilized in medical decision-making early in US outbreak the event that resource rationing had to be pursued at our institution. [Formula presented] [Formula presented]

8.
Open Forum Infectious Diseases ; 8(SUPPL 1):S243, 2021.
Article in English | EMBASE | ID: covidwho-1746718

ABSTRACT

Background. Although SARS-CoV-2 predominantly targets the respiratory system, it has also been associated with vascular complications including stroke. Identifying COVID-19 patients at elevated risk for stroke can help inform target anticoagulation strategies. We sought to understand how symptoms and laboratory markers at presentation with COVID-19 relate to stroke risk. Methods. We enrolled a cohort of 1324 subjects who were hospitalized with COVID-19 across six PennMedicine hospitals between April and August 2020 and performed retrospective, manual chart review to measure exposures including presenting symptoms and admission inflammatory markers. Data were organized with a REDCap database, and analyses were performed using R statistical software, with Bayesian binomial regression models fit using Stan Hamiltonian Monte Carlo via the "brms" package. Results. Among 1324 subjects, 19 stroke events were observed within 30 days of COVID-19 diagnosis. Admission inflammatory markers, including C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), ferritin, and D-dimer, were poor predictors of stroke risk. Among presenting symptoms, including respiratory, gastrointestinal, dermatologic, and neurologic features of COVID-19 disease, only altered mental status documented on presentation (in 529 subjects) was significantly associated with stroke risk (odds ratio 6.06, 95% credible interval 2.16 - 18.7). Conclusion. Inflammatory markers associated with COVID-19 disease severity did not discriminate patients at high versus low risk of stroke in this cohort. Altered mental status documented on presentation was significantly associated with incident stroke during COVID-19 disease.

10.
International Journal of Infectious Diseases ; 116:S20-S20, 2022.
Article in English | PMC | ID: covidwho-1717728
11.
Irish Medical Journal ; 114(9), 2021.
Article in English | Scopus | ID: covidwho-1710562
12.
J Eur Acad Dermatol Venereol ; 36(5): e332-e334, 2022 05.
Article in English | MEDLINE | ID: covidwho-1624575
13.
Ozone Science & Engineering ; 43(4):296-305, 2021.
Article in English | CAB Abstracts | ID: covidwho-1575846

ABSTRACT

SARS-CoV-2 has resulted in a global pandemic resulting in the infections of many millions and deaths of well over a million people. The ease of SARS-CoV-2 spread and the infectious nature of the virus in humans has resulted in an urgent need for effective disinfection strategies. Ozone (O3) is a promising disinfectant for SARS-CoV-2 due to its ability to overcome limitations with topical disinfection or sanitation products. In this work, we utilized RT-qPCR to measure RNA from a recombinant mammalian cell product, bacteriophage MS2, and SARS-CoV-2 sourced from municipal wastewater, after exposure to 4.5 and 9 ppmv O3.

14.
J Hosp Infect ; 115: 44-50, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1258420

ABSTRACT

Hospital-onset COVID-19 infections (HOCIs) are associated with excess morbidity and mortality in patients and healthcare workers. The aim of this review was to explore and describe the current literature in HOCI surveillance. Medline, EMBASE, the Cochrane Database of Systematic Reviews, the Cochrane Register of Controlled Trials, and MedRxiv were searched up to 30 November 2020 using broad search criteria. Articles of HOCI surveillance systems were included. Data describing HOCI definitions, HOCI incidence, types of HOCI identification surveillance systems, and level of system implementation were extracted. A total of 292 citations were identified. Nine studies on HOCI surveillance were included. Six studies reported on the proportion of HOCI among hospitalized COVID-19 patients, which ranged from 0 to 15.2%. Six studies provided HOCI case definitions. Standardized national definitions provided by the UK and US governments were identified. Four studies included healthcare workers in the surveillance. One study articulated a multimodal strategy of infection prevention and control practices including HOCI surveillance. All identified HOCI surveillance systems were implemented at institutional level, with eight studies focusing on all hospital inpatients and one study focusing on patients in the emergency department. Multiple types of surveillance were identified. Four studies reported automated surveillance, of which one included real-time analysis, and one included genomic data. Overall, the study quality was limited by the observational nature with short follow-up periods. In conclusion, HOCI case definitions and surveillance methods were developed pragmatically. Whilst standardized case definitions and surveillance systems are ideal for integration with existing routine surveillance activities and adoption in different settings, we acknowledged the difficulties in establishing such standards in the short-term.


Subject(s)
COVID-19 , Cross Infection , Cross Infection/epidemiology , Cross Infection/prevention & control , Hospitals , Humans , SARS-CoV-2 , Systematic Reviews as Topic
15.
Clinical Microbiology & Infection ; 16:16, 2021.
Article in English | MEDLINE | ID: covidwho-1209427

ABSTRACT

OBJECTIVES: We investigated the impact of COVID-19 and national pandemic response on primary care antibiotic prescribing in London. METHODS: Individual prescribing records between 2015 and 2020 for 2 million residents in north west London were analysed. Prescribing records were linked to SARS-CoV-2 test results. Prescribing volumes, in total, and stratified by patient characteristics, antibiotic class and AWaRe classification, were investigated. Interrupted time series analysis was performed to detect measurable change in the trend of prescribing volume since the national lockdown in March 2020, immediately before the first COVID-19 peak in London. RESULTS: Records covering 366 059 patients, 730 001 antibiotic items and 848 201 SARS-CoV-2 tests between January and November 2020 were analysed. Before March 2020, there was a background downward trend (decreasing by 584 items/month) in primary care antibiotic prescribing. This reduction rate accelerated to 3504 items/month from March 2020. This rate of decrease was sustained beyond the initial peak, continuing into winter and the second peak. Despite an overall reduction in prescribing volume, co-amoxiclav, a broad-spectrum "Access" antibiotic, prescribing rose by 70.1% in patients aged 50 and older from February to April. Commonly prescribed antibiotics within 14 days of a positive SARS-CoV-2 test were amoxicillin (863/2474, 34.9%) and doxycycline (678/2474, 27.4%). This aligned with national guidelines on management of community pneumonia of unclear cause. The proportion of "Watch" antibiotics used decreased during the peak in COVID-19. DISCUSSION: A sustained reduction in community antibiotic prescribing has been observed since the first lockdown. Investigation of community-onset infectious diseases and potential unintended consequences of reduced prescribing is urgently needed.

16.
Journal of the National Medical Association ; 112(5):S15, 2020.
Article in English | EMBASE | ID: covidwho-988445

ABSTRACT

Background: Due to the limited availability of rapid testing for SARS-CoV-2 infection, these tests are often reserved for those requiring urgent procedures or hospital admission and are often not available to emergency department (ED) patients. Complete blood count (CBC), C-reactive protein (CRP) and Ferritin levels can be easily obtained in the ED. Lymphopenia and high C-reactive protein and Ferritin levels are associated with poor outcome in COVID-19 illness. However, it is not known whether these biomarkers are useful for identifying persons with SARS-CoV-2 infection. Methods: We performed a cross-sectional study of patients 18 years or older who were evaluated at an academic ED for suspected SARS-CoV-2 infection from March to May 2020. CBC, CRP and Ferritin levels were ordered at clinician’s discretion in patients who were suspected to have SARS-CoV-2 infection. SARS-CoV-2 infection was diagnosed using a number of PCR-based tests including the Cepheid Xpert Xpress and the Diasorin Simplexa. The discriminative values of the candidate biomarkers were estimated using the area under the receiver operating characteristic curve (AUC). Results: We studied a total of 1082 patients who had a median age of 59.5 (IQR: 46.0 – 71.0) years. A total of 431 (39.8%) of the subjects had PCR confirmed SARS-CoV-2 infection. The median absolute lymphocyte count was 0.9 (IQR: 0.7 – 1.3) and 1.0 (0.7 – 1.6) in those with and those without SARS-CoV-2 infection respectively (p=0.0004). The median CRP level in mg/L was 8.9 (IQR: 4.6 – 17.3) and 6.1 (IQR: 1.6 – 14.0) in those with and those without SARS-CoV-2 infection respectively (p=0.0001). The median ferritin level in ng/mL was 782 (IQR: 299 – 1479) and 312 (IQR: 106 – 1015) in those with and those without SARS-CoV-2 infection respectively (p=0.0001). Lymphocyte count, CRP and Ferritin levels distinguished between those with and those without SARS-CoV-2 infection with AUCs of 0.56 (IQR: 0.53 – 0.60), 0.61 (IQR: 0.58 – 0.64) and 0.66 (IQR: 0.62 – 0.68). Conclusion: Although patients with SARS-CoV-2 infection have lymphopenia and elevated CRP and ferritin levels, the levels of these biomarkers are not useful for identifying persons under investigation who have SARS-CoV-2 infection.

17.
Int J Infect Dis ; 100: 278-282, 2020 Nov.
Article in English | MEDLINE | ID: covidwho-959810

ABSTRACT

Research, collaboration, and knowledge exchange are critical to global efforts to tackle antimicrobial resistance (AMR). Different healthcare economies are faced with different challenges in implementing effective strategies to address AMR. Building effective capacity for research to inform AMR-related strategies and policies is recognised as an important contributor to success. Interdisciplinary, intersector, as well as international collaborations are needed to span global to local efforts to tackle AMR. The development of reciprocal, long-term partnerships between collaborators in high-income and in low- and middle-income countries (LMICs) needs to be built on principles of capacity building. Using case studies spanning local and international research collaborations to codesign, implement, and evaluate strategies to tackle AMR, we have evaluated and build upon the ESSENCE criteria for capacity building in LMICs. The first case study describes the local codesign and implementation of antimicrobial stewardship (AMS) in the state of Kerala in India. The second case study describes an international research collaboration investigating AMR surgical patient pathways in India, the UK, and South Africa. We describe the steps undertaken to develop robust, agile, and flexible AMS research and implementation teams. Notably, investing in capacity building ensured that the programmes described in these case studies were sustained through the current severe acute respiratory syndrome coronavirus pandemic. Describing the strategies adopted by a local and an international collaboration to tackle AMR, we provide a model for capacity building in LMICs that can support sustainable and agile AMS programmes.


Subject(s)
Anti-Bacterial Agents/pharmacology , Antimicrobial Stewardship , Biomedical Research , Drug Resistance, Bacterial , Capacity Building , Humans , Income , India , International Cooperation , South Africa , United Kingdom
18.
Annals of Emergency Medicine ; 76(4):S25, 2020.
Article in English | EMBASE | ID: covidwho-898384

ABSTRACT

Study Objectives: Emergency department (ED) revisits are associated with significant resource utilization. Accordingly, revisits serve as an important quality measure for emergency care. In recent times, EDs have been challenged by critical resource constraints in the setting of the COVID-19 pandemic. When appropriate, medically stable COVID-19 patients are discharged home rather than admitted for further care. However, the natural history of COVID-19 is not well understood and patients may quickly progress to requiring medical attention. To our knowledge, ED revisits have not been previously characterized in the setting of COVID-19. We aim to quantify the incidence of, as well as determine risk factors for, ED revisits for COVID-19 patients. Methods: We conducted retrospective study of 323 reverse-transcription polymerase chain reaction-confirmed COVID-19 patients who presented to a single academic tertiary-care institution from March 15 to April 15 of 2020. Demographic and clinical information was abstracted from the electronic medical record. Predictor variables (age, history of hypertension, diabetes, asthma, chronic obstructive pulmonary disease, current tobacco or marijuana use) were selected based on current knowledge of risk factors for severe COVID-19 illness. All return visits to the ED within 28 days of index ED presentation were classified as revisits. Multivariable logistic regression models were used to identify independent demographic and clinical risk factors for ED revisits. We also performed exploratory univariable analyses of a subset of 179 patients who had measured serum biomarkers (absolute neutrophil count (ANC), alanine aminotransferase (ALT), ferritin, C-reactive protein, D-dimer, lactate dehydrogenase (LDH)) in order to identify potential biochemical risk factors for ED revisits. Results: Of the 323 patients studied, 98 were discharged from the ED during their index visit and 225 were admitted to the hospital. Among those discharged, 25/98 (25.5%) returned within 28 days of index ED presentation. Median time to revisit was 3 days (interquartile range (IQR): 2 to 7). Among those admitted during their index visit (median hospital length of stay: 6 days), 26/225 (11.6%) returned within 28 days of index ED presentation. Median time to revisit for this group was 14.5 days (IQR: 5 to 22). Cumulative incidence of ED revisits was 15.8% (95% CI: 12.2 to 20.2). Patients with and without ED revisits were similar across demographic and clinical variables examined, with the exceptions of tobacco or marijuana use and history of COPD. Both tobacco or marijuana use (odds ratio (OR): 2.9, 95% CI: 1.1 to 7.6) and history of COPD (OR: 3.1, 95% CI: 1.1 to 8.8) were found to be independent risk factors for ED revisits. In our exploratory analysis of patients with biomarker data, ANC (OR: 0.808, 95% CI: 0.689 to 0.948), ALT (OR: 0.973, 95% CI: 0.953 to 0.993), and LDH (OR: 0.996, 95% CI: 0.992 to 0.999) were found to be associated with ED revisits. Conclusion: The incidence of ED revisits in our COVID-19 cohort was 15.8% (95% CI: 12.2 to 20.2). Risk factors for revisits included current tobacco or marijuana use and history of COPD. Preliminary study suggests the utility of serum biomarker data in helping to stratify revisit risk. In future analysis we will determine the reasons for ED revisits as well as develop a model for identifying those at risk for ED revisits.

19.
Annals of Emergency Medicine ; 76(4):S17, 2020.
Article in English | EMBASE | ID: covidwho-898378

ABSTRACT

Study Objectives: Concerns over the use of non-steroidal anti-inflammatory drugs (NSAIDs) for the management of fever and myalgia in COVID-19 patients were raised after four cases of critical illness in young, otherwise healthy patients who took NSAIDS were observed in France. France’s health minister subsequently made a recommendation to use acetaminophen in lieu of ibuprofen. However, the association between NSAID use and outcomes in COVID-19 illness has not been adequately studied. The objective of this study is to determine whether an association exists between prior NSAID use and COVID-19 illness severity. Methods: We performed a single-center retrospective cohort study of consecutive adult patients diagnosed in the emergency department (ED) with PCR confirmed SARS-Cov-2 infection. NSAID use was ascertained based on a review of the medication list found in patients’ electronic medical records. Our primary outcome was critical COVID-19 illness, defined as a composite of death, respiratory failure requiring intubation, and shock requiring vasopressors, occurring within 28 days of ED presentation. We modeled the association between NSAID use and our primary outcome using logistic regression, and adjusting for hypertension, diabetes, asthma, chronic obstructive pulmonary disease (COPD), other chronic lung disease, obstructive sleep apnea, immunocompromised status, angiotensin converting enzyme inhibitor (ACE-I) or aldosterone receptor blocker (ARB) use, anticoagulation use, and immunosuppressant use. Results: Among the 422 patients studied, 88 (21%) were on NSAIDS prior to acquiring COVID-19 and a total of 89 patients (21%) developed critical COVID-19 illness within 28 days of ED presentation. Among those using NSAIDs, 18 (20%) developed critical illness. Of the 11 predictor variables examined, hypertension (odds ratio = 1.04 (95% CI: 0.38 - 1.71)), diabetes (0.97 (95% CI: 0.42 - 1.52)), and chronic lung disease (1.20 (0.20 - 2.20)) were significantly associated with increased risk of critical COVID-19 illness (Table 1). NSAID use was not found to be an independent predictor of critical COVID-19 illness (odds ratio = 0.05 (95% CI;-0.57 - 0.73). Conclusion: To our knowledge, this is the first study of the association between NSAID use and critical COVID-19 illness. Our results demonstrate that NSAID use does not significantly increase the risk of critical COVID-19 illness. This study is limited by lack of prospective ascertainment of NSAID use. Prospective evaluation of evaluate outcomes among COVID-19 patients with NSAID use is warranted. [Formula presented]

20.
European Journal of Public Health ; 30(Supplement_5), 2020.
Article | Mary Ann Liebert | ID: covidwho-814133

ABSTRACT

Background Public health agencies had to respond swiftly to the novel coronavirus that emerged in 2019 (COVID-19) to try to contain the virus, which requires early identification of new cases. Monitoring exposed individuals is labor intensive and available tools are often limited. MITRE, a company that operates federally funded research and development centers for the U.S. government, rapidly developed a configurable monitoring tool that allows public health authorities to monitor potentially exposed individuals in their jurisdictions. Methods A team, including public health leaders, field epidemiologists, software engineers, and health communication specialists, was quickly assembled to design and develop an open source, disease-independent monitoring tool called Sara Alert. Outreach to key public health stakeholders, including partner organizations and local and state health departments, was conducted early for requirements gathering and to validate assumptions. Public health law experts were consulted regarding data privacy and security. Results By four weeks, a minimally viable monitoring tool was available for testing by public health partners. Exposed individuals can be enrolled and reminded daily to enter a temperature and any symptoms by web or mobile interface, SMS messaging or phone. Public health officials monitor and can quickly take action if symptoms consistent with COVID-19 are reported of if there is failure to report within a configurable time frame. Dashboards provide insight into aggregated data appropriate to level of view. Conclusions Sara Alert serves as a force multiplier that supports disease containment and allows resources to be directed where they are most needed. Successful development was possible because key stakeholders across public health practice were consulted early. Sara Alert is available, free, to state and local public health departments and serves as an enduring resource easily configured for the next public health emergency. Key messages Sara Alert serves as a force multiplier that supports disease containment and allows resources to be directed where they are most needed. Sara Alert serves as an enduring resource easily configured for the next public health emergency.

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