A Mobile App and Dashboard for Early Detection of Infectious Disease Outbreaks: Development Study

BackgroundOutbreaks of infectious diseases pose great risks, including hospitalization and death, to public health. Therefore, improving the management of outbreaks is important for preventing widespread infection and mitigating associated risks. Mobile health technology provides new capabilities that can help better capture, monitor, and manage infectious diseases, including the ability to quickly identify potential outbreaks.ObjectiveThis study aims to develop a new infectious disease surveillance (IDS) system comprising a mobile app for accurate data capturing and dashboard for better health care planning and decision making.MethodsWe developed the IDS system using a 2-pronged approach: a literature review on available and similar disease surveillance systems to understand the fundamental requirements and face-to-face interviews to collect specific user requirements from the local public health unit team at the Nepean Hospital, Nepean Blue Mountains Local Health District, New South Wales, Australia.ResultsWe identified 3 fundamental requirements when designing an electronic IDS system, which are the ability to capture and report outbreak data accurately, completely, and in a timely fashion. We then developed our IDS system based on the workflow, scope, and specific requirements of the public health unit team. We also produced detailed design and requirement guidelines. In our system, the outbreak data are captured and sent from anywhere using a mobile device or a desktop PC (web interface). The data are processed using a client-server architecture and, therefore, can be analyzed in real time. Our dashboard is designed to provide a daily, weekly, monthly, and historical summary of outbreak information, which can be potentially used to develop a future intervention plan. Specific information about certain outbreaks can also be visualized interactively to understand the unique characteristics of emerging infectious diseases.ConclusionsWe demonstrated the design and development of our IDS system. We suggest that the use of a mobile app and dashboard will simplify the overall data collection, reporting, and analysis processes, thereby improving the public health responses and providing accurate registration of outbreak information. Accurate data reporting and collection are a major step forward in creating a better intervention plan for future outbreaks of infectious diseases.     

Novel Methods in the Surveillance of Influenza-Like Illness in Germany Using Data From a Symptom Assessment App (Ada): Observational Case Study

BackgroundParticipatory epidemiology is an emerging field harnessing consumer data entries of symptoms. The free app Ada allows users to enter the symptoms they are experiencing and applies a probabilistic reasoning model to provide a list of possible causes for these symptoms.ObjectiveThe objective of our study is to explore the potential contribution of Ada data to syndromic surveillance by comparing symptoms of influenza-like illness (ILI) entered by Ada users in Germany with data from a national population-based reporting system called GrippeWeb.MethodsWe extracted data for all assessments performed by Ada users in Germany over 3 seasons (2017/18, 2018/19, and 2019/20) and identified those with ILI (report of fever with cough or sore throat). The weekly proportion of assessments in which ILI was reported was calculated (overall and stratified by age group), standardized for the German population, and compared with trends in ILI rates reported by GrippeWeb using time series graphs, scatterplots, and Pearson correlation coefficient.ResultsIn total, 2.1 million Ada assessments (for any symptoms) were included. Within seasons and across age groups, the Ada data broadly replicated trends in estimated weekly ILI rates when compared with GrippeWeb data (Pearson correlation—2017-18: r=0.86, 95% CI 0.76-0.92; P<.001; 2018-19: r=0.90, 95% CI 0.84-0.94; P<.001; 2019-20: r=0.64, 95% CI 0.44-0.78; P<.001). However, there were differences in the exact timing and nature of the epidemic curves between years.ConclusionsWith careful interpretation, Ada data could contribute to identifying broad ILI trends in countries without existing population-based monitoring systems or to the syndromic surveillance of symptoms not covered by existing systems.     

Early Detection of Influenza Activity Using Syndromic Surveillance in Missouri

Objective

To assess how weekly percent of influenza-like illness (ILI) reported via Early Notification of Community-based Epidemics (ESSENCE) tracked weekly counts of laboratory confirmed influenza cases in five influenza seasons in order to evaluate the early warning potential of ILI in ESSENCE and improve ongoing influenza surveillance efforts in Missouri.

Introduction

Syndromic surveillance is used routinely to detect outbreaks of disease earlier than traditional methods due to its ability to automatically acquire data in near real-time. Missouri has used emergency department (ED) visits to monitor and track seasonal influenza activity since 2006.

Methods

The Missouri ESSENCE system utilizes data from 84 hospitals, which represents up to 90 percent of all ED visits occurring in Missouri statewide each day. The influenza season is defined as starting during Centers for Disease Control and Prevention (CDC) week number 40 (around the first of October) and ending on CDC week 20 of the following year, which is usually at the end of May.A confirmed influenza case is laboratory confirmed by viral culture, rapid diagnostic tests, or a four-fold rise in antibody titer between acute and convalescent serum samples. Laboratory results are reported on a weekly basis. To assess the severity of influenza activity, all flu seasons were compared with the 2008–09 season, which experienced the lowest influenza activity based on laboratory data. Analysis of variance (ANOVA) was applied for this analysis using Statistical Analysis Software (SAS) (version 9.2).The standard ESSENCE ILI subsyndrome includes ED chief complaints that contain keywords such as “flu”, “flulike”, “influenza” or “fever plus cough” or “fever plus sore throat”. The ESSENCE ILI weekly percent is the number of ILI visits divided by total ED visits.Time series of weekly percent of ILI in ESSENCE were compared to weekly counts of laboratory confirmed influenza cases. Spearman correlation coefficients were calculated using SAS. The baseline refers to the mean of three flu seasons with low influenza activity (2006–07, 2008–09 and 2010–11 seasons). The threshold was calculated as this baseline plus three standard deviations.The early warning potential of the ESSENCE weekly ILI percent was evaluated for five consecutive influenza seasons, beginning in 2006. This was accomplished by calculating the time lag between the first ESSENCE ILI warning versus the first lab confirmed influenza warning. A warning was identified if either lab confirmed case counts or weekly percent of ILI crossed over their respective baselines.

Results

For each influenza season evaluated, weekly ILI rates reported via ESSENCE were significantly correlated with weekly counts of laboratory-confirmed influenza cases (Figure 1 shows that two influenza seasons (2007–08 and 2009–10) were more severe than others examined based on the ESSENCE percent ILI threshold analysis, this result is consistent with the examination of severity of influenza activity based on lab confirmed influenza data (p<0.05).Open in a separate windowFigure 1Number and baseline of lab confirmed influenza cases, ESSENCE weekly ILI percent and baseline, and ESSENCE ILI threshold for five consecutive influenza seasons, 2006–2011.

Table 1

Correlation between laboratory confrmed influenza cases and ESSENCE ILI weekly percent in five influenza seasons, 2006–2011

2003-2004年福建省流感暴发监测分析

[目的]了解福建省流感流行动态,探索流行规律,为流感防治提供科学依据.[方法]进行流行病学调查,用MDCK细胞和鸡胚进行病毒分离,用血凝抑制实验对病毒株进行分型鉴定及血清流感抗体测定.[结果]2003-2004年我省共报告局部暴发流感疫情49起,发病3 088例,共采集咽拭子或漱口液标本360份,分离流感病毒阳性率25.8%(93/360).其中甲3型88株(94.6%),乙型5株(5.3%).2年共采集流感样患者急性期、恢复期血清各221份,其中甲3型抗体4倍增长阳性率58.4%(129/221),乙型抗体4倍增长阳性0.5%(11/221).[结论]引起福建省2003-2004年流感暴发的毒株以甲3型为主,暴发的时间主要集中在每年的4月和9月.     

福建省2004年登革热疫情分析

[目的]分析我省2004年登革热疫情,为防治措施提供依据。[方法]调查和分析2004年福建省登革热流行病学特点及影响因素。[结果]2004年登革热输入性病例全年都有,本土病例集中在9月下旬和10月上旬,与当地的蚊媒消长情况相一致,登革热流行株为登革热病毒Ⅰ型。[结论]我省与东南亚地区和我国南方登革热常年流行的省市人口流动频繁,输入性病例引起本土暴发流行的危险性极大。     

Early Detection of Nosocomial Outbreaks Caused by Rare Pathogens: A Case Study Employing Score Prediction Interval

ObjectivesNosocomial outbreaks involve only a small number of cases and limited baseline data. The present study proposes a method to detect the nosocomial outbreaks caused by rare pathogens, exploiting score prediction interval of a Poisson distribution.MethodsThe proposed method was applied to three empirical datasets of nosocomial outbreaks in Japan: outbreaks of (1) multidrug-resistant Acinetobacter baumannii (n = 46) from 2009 to 2010, (2) multidrug-resistant Pseudomonas aerginosa (n = 18) from 2009 to 2010, and (3) Serratia marcescens (n = 226) from 1999 to 2000.ResultsThe proposed method successfully detected all three outbreaks during the first 2 months. Both the model-based and empirically derived threshold values indicated that the nosocomial outbreak of rare infectious disease may be declared upon diagnosis of index case(s), although the sensitivity and specificity were highly variable.ConclusionThe findings support the practical notion that, upon diagnosis of index patient(s), one should immediately start the outbreak investigation of nosocomial outbreak caused by a rare pathogen. The proposed score prediction interval can permit easy computation of outbreak threshold in hospital settings among healthcare experts.     

Risk Factors Associated with a Dengue Fever Outbreak in Islamabad,Pakistan: Case-Control Study

BackgroundOn October 23, 2016, 79 dengue fever cases were reported from the Union Council Tarlai to Federal Disease Surveillance and Response Unit Islamabad. A team was established to investigate the suspected dengue outbreak.ObjectiveThe aim of this study was to determine the extent of the outbreak and identify the possible risk factors.MethodsActive case finding was performed through a house-to-house survey. A case was defined as an acute onset of fever ≥38℃ in a resident of Tarlai from October 2 to November 11, 2016, with a positive dengue virus (nonstructural protein, NS-1) test and any of the two of following signs and symptoms: retroorbital/ocular pain, headache, rash, myalgia, arthralgia, and hemorrhagic manifestations. A structured questionnaire was used to collect data. Age- and sex-matched controls (1:1) were identified from residents in the same area as cases. Blood samples were taken and sent to the National Institute of Health for genotype identification.ResultsDuring the active case search, 145 cases of dengue fever were identified by surveying 928 houses from October 23 to November 11, 2016. The attack rate (AR) was 17.0/10,000. The mean age was 34.4 (SD 14.4) years. More than half of the cases were male (80/145, 55.2%). Among all cases, 29% belonged to the 25-34 years age group and the highest AR was found in the 35-44 years age group (35.6/10,000), followed by the 55-64 years age group (35.5/10,000). All five blood samples tested positive for NS-1 (genotype DENV-2). The most frequent presenting signs/symptoms were fever and headache (both 100%). Stagnant water around houses (odds ratio [OR] 4.86, 95% CI 2.94-8.01; P<.001), presence of flower pots in the home (OR 2.73, 95% CI 1.67-4.45; P<.001), and open water containers (OR 2.24, 95% CI 1.36-3.60; P<.001) showed higher odds among cases. Conversely, use of bed nets (OR 0.44, 95% CI 0.25-0.77; P=.003), insecticidal spray (OR 0.33, 95% CI 0.22-0.55; P<.001), door screens (OR 0.27, 95% CI 0.15-0.46; P<.001), mosquito coil/mat (OR 0.26, 95% CI 0.16-0.44; P<.001), and cleanliness of the house (OR 0.12, 95% CI 0.05-0.26; P<.001) showed significant protective effects.ConclusionsStagnant water acting as breeding grounds for vectors was identified as the probable cause of spread of the dengue outbreak. Establishment of surveillance and an early reporting system along with use of protective measures against the vector are strongly recommended.     

广东潮州某部登革热、流行性乙型脑炎的监测及综合防制研究

目的 探索潮州某驻军登革热和流行性乙型脑炎(乙脑)等虫媒病综合防制效果，为预防和控制虫媒病毒病提供科学依据。方法收集发热可疑患者和健康人血标本及蚊虫标本作病毒分离和血清学抗体调查；按全面或随机法调查营区内蚊虫孳生情况，人诱法监测成蚊叮刺率；用C6／36细胞培养法分离病毒并用间接免疫荧光法(IFAT)或逆转录一聚合酶链反应(RT-PCR)法鉴定；用IFAT调查健康人群登革热和乙脑抗体；以“治本清源”为原则，普及防病知识和开展爱国卫生运动，针对不同孳生地类型和栖息特点采用不同方法处理。结果经监测发热待查病人和媒介蚊虫均未分离出病毒；健康人群登革热和乙脑的抗体水平不高；处理前蚊类优势种为白纹伊蚊和致倦库蚊，有少量三带喙库蚊和骚扰阿蚊，其中自纹伊蚊的容器指数(CI)为24．1，百户指数(BI)为30．0，均高于规定的危险地区界限20．0。结论该驻地存在登革热和乙脑暴发流行潜在危险，蚊虫密度较高，人群抗体水平低，采用综合防制措施后，经3年连续观察，蚊媒已控制在不足为害的水平。     

Performance of the Severe Acute Respiratory Illness Sentinel Surveillance System in Yemen: Mixed Methods Evaluation Study

BackgroundThe national severe acute respiratory illness (SARI) surveillance system in Yemen was established in 2010 to monitor SARI occurrence in humans and provide a foundation for detecting SARI outbreaks.ObjectiveTo ensure that the objectives of national surveillance are being met, this study aimed to examine the level of usefulness and the performance of the SARI surveillance system in Yemen.MethodsThe updated Centers for Disease Control and Prevention guidelines were used for the purposes of our evaluation. Related documents and reports were reviewed. Data were collected from 4 central-level managers and stakeholders and from 10 focal points at 4 sentinel sites by using a semistructured questionnaire. For each attribute, percent scores were calculated and ranked as follows: very poor (≤20%), poor (20%-40%), average (40%-60%), good (60%-80%), and excellent (>80%).ResultsAs rated by the evaluators, the SARI surveillance system achieved its objectives. The system’s flexibility (percent score: 86%) and acceptability (percent score: 82%) were rated as “excellent,” and simplicity (percent score: 74%) and stability (percent score: 75%) were rated as “good.” The percent score for timeliness was 23% in 2018, which indicated poor timeliness. The overall data quality percent score of the SARI system was 98.5%. Despite its many strengths, the SARI system has some weaknesses. For example, it depends on irregular external financial support.ConclusionsThe SARI surveillance system was useful in estimating morbidity and mortality, monitoring the trends of the disease, and promoting research for informing prevention and control measures. The overall performance of the SARI surveillance system was good. We recommend expanding the system by promoting private health facilities’ (eg, private hospitals and private health centers) engagement in SARI surveillance, establishing an electronic database at central and peripheral sites, and providing the National Central Public Health Laboratory with the reagents needed for disease confirmation.     

1991年中山市沙溪镇登革热局部流行的调查

1991年8月下旬,中山市沙溪镇圣狮村发生登革热。流行初期,由于患者症状不够典型及调查工作不够深入细致,致误诊,未能及时采取有效的防疫措施,造成疫情扩散蔓延,波及紧邻的龙头环、龙聚环、象角三村及圩镇。整个流行历时64天,共发生112例。本次流行经病原学证实为I型登革病毒所引起。本文还就传染来源、传播因素及临床表现与致病毒株型别的关系等问题进行了讨论。     

Reasons for Nonuse,Discontinuation of Use,and Acceptance of Additional Functionalities of a COVID-19 Contact Tracing App: Cross-sectional Survey Study

BackgroundIn several countries, contact tracing apps (CTAs) have been introduced to warn users if they have had high-risk contacts that could expose them to SARS-CoV-2 and could, therefore, develop COVID-19 or further transmit the virus. For CTAs to be effective, a sufficient critical mass of users is needed. Until now, adoption of these apps in several countries has been limited, resulting in questions on which factors prevent app uptake or stimulate discontinuation of app use.ObjectiveThe aim of this study was to investigate individuals’ reasons for not using, or stopping use of, a CTA, in particular, the Coronalert app. Users’ and nonusers’ attitudes toward the app’s potential impact was assessed in Belgium. To further stimulate interest and potential use of a CTA, the study also investigated the population’s interest in new functionalities.MethodsAn online survey was administered in Belgium to a sample of 1850 respondents aged 18 to 64 years. Data were collected between October 30 and November 2, 2020. Sociodemographic differences were assessed between users and nonusers. We analyzed both groups’ attitudes toward the potential impact of CTAs and their acceptance of new app functionalities.ResultsOur data showed that 64.9% (1201/1850) of our respondents were nonusers of the CTA under study; this included individuals who did not install the app, those who downloaded but did not activate the app, and those who uninstalled the app. While we did not find any sociodemographic differences between users and nonusers, attitudes toward the app and its functionalities seemed to differ. The main reasons for not downloading and using the app were a perceived lack of advantages (308/991, 31.1%), worries about privacy (290/991, 29.3%), and, to a lesser extent, not having a smartphone (183/991, 18.5%). Users of the CTA agreed more with the potential of such apps to mitigate the consequences of the pandemic. Overall, nonusers found the possibility of extending the CTA with future functionalities to be less acceptable than users. However, among users, acceptability also tended to differ. Among users, functionalities relating to access and control, such as digital certificates or “green cards” for events, were less accepted (358/649, 55.2%) than functionalities focusing on informing citizens about the spread of the virus (453/649, 69.8%) or making an appointment to get tested (525/649, 80.9%).ConclusionsOur results show that app users were more convinced of the CTA’s utility and more inclined to accept new app features than nonusers. Moreover, nonusers had more CTA-related privacy concerns. Therefore, to further stimulate app adoption and use, its potential advantages and privacy-preserving mechanisms need to be stressed. Building further knowledge on the forms of resistance among nonusers is important for responding to these barriers through the app’s further development and communication campaigns.     

Development and Validation of Indicators for Population Injury Surveillance in Hong Kong: Development and Usability Study

BackgroundInjury is an increasingly pressing global health issue. An effective surveillance system is required to monitor the trends and burden of injuries.ObjectiveThis study aimed to identify a set of valid and context-specific injury indicators to facilitate the establishment of an injury surveillance program in Hong Kong.MethodsThis development of indicators adopted a multiphased modified Delphi research design. A literature search was conducted on academic databases using injury-related search terms in various combinations. A list of potential indicators was sent to a panel of experts from various backgrounds to rate the validity and context-specificity of these indicators. Local hospital data on the selected core indicators were used to examine their applicability in the context of Hong Kong.ResultsWe reviewed 142 articles and identified 55 indicators, which were classified into 4 domains. On the basis of the ratings by the expert panel, 13 indicators were selected as core indicators because of their good validity and high relevance to the local context. Among these indicators, 10 were from the construct of health care service use, and 3 were from the construct of postdischarge outcomes. Regression analyses of local hospitalization data showed that the Hong Kong Safe Community certification status had no association with 5 core indicators (admission to intensive care unit, mortality rate, length of intensive care unit stay, need for a rehabilitation facility, and long-term behavioral and emotional outcomes), negative associations with 4 core indicators (operative intervention, infection rate, length of hospitalization, and disability-adjusted life years), and positive associations with the remaining 4 core indicators (attendance to accident and emergency department, discharge rate, suicide rate, and hospitalization rate after attending the accident and emergency department). These results confirmed the validity of the selected core indicators for the quantification of injury burden and evaluation of injury-related services, although some indicators may better measure the consequences of severe injuries.ConclusionsThis study developed a set of injury outcome indicators that would be useful for monitoring injury trends and burdens in Hong Kong.     

Number Needed to Benefit From Information (NNBI): Proposal From a Mixed Methods Research Study With Practicing Family Physicians

PURPOSE

We wanted to describe family physicians’ use of information from an electronic knowledge resource for answering clinical questions, and their perception of subsequent patient health outcomes; and to estimate the number needed to benefit from information (NNBI), defined as the number of patients for whom clinical information was retrieved for 1 to benefit.

METHODS

We undertook a mixed methods research study, combining quantitative longitudinal and qualitative research studies. Participants were 41 family physicians from primary care clinics across Canada. Physicians were given access to 1 electronic knowledge resource on handheld computer in 2008–2009. For the outcome assessment, participants rated their searches using a validated method. Rated searches were examined during interviews guided by log reports that included ratings. Cases were defined as clearly described searches where clinical information was used for a specific patient. For each case, interviewees described information-related patient health outcomes. For the mixed methods data analysis, quantitative and qualitative data were merged into clinical vignettes (each vignette describing a case). We then estimated the NNBI.

RESULTS

In 715 of 1,193 searches for information conducted during an average of 86 days, the search objective was directly linked to a patient. Of those searches, 188 were considered to be cases. In 53 cases, participants associated the use of information with at least 1 patient health benefit. This finding suggested an NNBI of 14 (715/53).

CONCLUSION

The NNBI may be used in further experimental research to compare electronic knowledge resources. A low NNBI can encourage clinicians to search for information more frequently. If all searches had benefits, the NNBI would be 1. In addition to patient benefits, learning and knowledge reinforcement outcomes are frequently reported.     

Improving Detection of Disease Re-emergence Using a Web-Based Tool (RED Alert): Design and Case Analysis Study

BackgroundCurrently, the identification of infectious disease re-emergence is performed without describing specific quantitative criteria that can be used to identify re-emergence events consistently. This practice may lead to ineffective mitigation. In addition, identification of factors contributing to local disease re-emergence and assessment of global disease re-emergence require access to data about disease incidence and a large number of factors at the local level for the entire world. This paper presents Re-emerging Disease Alert (RED Alert), a web-based tool designed to help public health officials detect and understand infectious disease re-emergence.ObjectiveOur objective is to bring together a variety of disease-related data and analytics needed to help public health analysts answer the following 3 primary questions for detecting and understanding disease re-emergence: Is there a potential disease re-emergence at the local (country) level? What are the potential contributing factors for this re-emergence? Is there a potential for global re-emergence?MethodsWe collected and cleaned disease-related data (eg, case counts, vaccination rates, and indicators related to disease transmission) from several data sources including the World Health Organization (WHO), Pan American Health Organization (PAHO), World Bank, and Gideon. We combined these data with machine learning and visual analytics into a tool called RED Alert to detect re-emergence for the following 4 diseases: measles, cholera, dengue, and yellow fever. We evaluated the performance of the machine learning models for re-emergence detection and reviewed the output of the tool through a number of case studies.ResultsOur supervised learning models were able to identify 82%-90% of the local re-emergence events, although with 18%-31% (except 46% for dengue) false positives. This is consistent with our goal of identifying all possible re-emergences while allowing some false positives. The review of the web-based tool through case studies showed that local re-emergence detection was possible and that the tool provided actionable information about potential factors contributing to the local disease re-emergence and trends in global disease re-emergence.ConclusionsTo the best of our knowledge, this is the first tool that focuses specifically on disease re-emergence and addresses the important challenges mentioned above.     

App Use and Usability of a Barcode-Based Digital Platform to Augment COVID-19 Contact Tracing: Postpilot Survey and Paradata Analysis

BackgroundThe COVID-19 pandemic has drastically changed life in the United States, as the country has recorded over 23 million cases and 383,000 deaths to date. In the leadup to widespread vaccine deployment, testing and surveillance are critical for detecting and stopping possible routes of transmission. Contact tracing has become an important surveillance measure to control COVID-19 in the United States, and mobile health interventions have found increased prominence in this space.ObjectiveThe aim of this study was to investigate the use and usability of MyCOVIDKey, a mobile-based web app to assist COVID-19 contact tracing efforts, during the 6-week pilot period.MethodsA 6-week study was conducted on the Vanderbilt University campus in Nashville, Tennessee. The study participants, consisting primarily of graduate students, postdoctoral researchers, and faculty in the Chemistry Department at Vanderbilt University, were asked to use the MyCOVIDKey web app during the course of the study period. Paradata were collected as users engaged with the MyCOVIDKey web app. At the end of the study, all participants were asked to report on their user experience in a survey, and the results were analyzed in the context of the user paradata.ResultsDuring the pilot period, 45 users enrolled in MyCOVIDKey. An analysis of their enrollment suggests that initial recruiting efforts were effective; however, participant recruitment and engagement efforts at the midpoint of the study were less effective. App use paralleled the number of users, indicating that incentives were useful for recruiting new users to sign up but did not result in users attempting to artificially inflate their use as a result of prize offers. Times to completion of key tasks were low, indicating that the main features of the app could be used quickly. Of the 45 users, 30 provided feedback through a postpilot survey, with 26 (58%) completing it in its entirety. The MyCOVIDKey app as a whole was rated 70.0 on the System Usability Scale, indicating that it performed above the accepted threshold for usability. When the key-in and self-assessment features were examined on their own, it was found that they individually crossed the same thresholds for acceptable usability but that the key-in feature had a higher margin for improvement.ConclusionsThe MyCOVIDKey app was found overall to be a useful tool for COVID-19 contact tracing in a university setting. Most users suggested simple-to-implement improvements, such as replacing the web app framework with a native app format or changing the placement of the scanner within the app workflow. After these updates, this tool could be readily deployed and easily adapted to other settings across the country. The need for digital contact tracing tools is becoming increasingly apparent, particularly as COVID-19 case numbers continue to increase while more businesses begin to reopen.