Effectiveness of implementing evidence-based approaches to promote physical activity in a Midwestern micropolitan area using a quasi-experimental hybrid type I study design.

BACKGROUND: Much evidence-based physical activity (PA) interventions have been tested and implemented in urban contexts. However, studies that adapt, implement, and evaluate the effectiveness of these interventions in micropolitan rural contexts are needed. The study aimed to evaluate the effectiveness of the Active Ottumwa intervention to promote PA in a micropolitan community. METHODS: Between 2013 - 2019, we implemented Active Ottumwa in a micropolitan setting, and subsequently implemented and evaluated its effectiveness using a Hybrid Type I design. In this paper, we describe the intervention's effectiveness in promoting PA. We collected PA data over 24 months from a cohort of community residents using accelerometers and PA data from two cross-sectional community surveys administered in 2013 and 2018, using the Global Physical Activity Questionnaire. RESULTS: From the cohort, we found significant change in PA over 24 months (P = 0.03) corresponding to a 45-min daily decrease in sedentary activity, a daily increase of 35-min in light PA and 9 min in moderate-to-vigorous PA. There was a statistically significant (P = 0.01) increasing trend at the population-level in the moderate-to-vigorous composition of 7 min between the two cross-sectional assessments (95% CI: 0.1%-1.34%). CONCLUSIONS: The study demonstrates that the adapted evidence-based PA interventions in a micropolitan context is effective.

The Association Between State Characteristics and Latinx People's Treated Hypertension in Established and New Latinx Destination States: A Multilevel Analysis.

This study sought to quantify the contributions of state-level factors including income inequality, state's legislature political control, and Medicaid expansion in new and established Latinx destination states on Latinx individuals' treated hypertension. Mixed-effects logistic regression analyses were conducted to analyze 2017 Behavioral Risk Factor Surveillance System data from 7524 Latinx adults nested within 39 states. Overall, 70% reported being pharmacologically treated for hypertension, and 66% resided in established destination states. Compared with Latinx people in established destination states, Latinx people in new destinations had lower odds of having treated hypertension (odds ratio [OR] = 0.72, 95% CI = 0.54-0.95). Within established Latinx destinations, the odds of treated hypertension were lower in states where legislatures expanded Medicaid than in states that did not expand Medicaid (OR = 0.84, 95% CI = 0.79-0.89). However, after controlling for the effects of individual-level factors, this association was no longer statistically significant. In new Latinx destination states, Medicaid expansion, legislatures' political control, and income inequality were not associated with treated hypertension. The study results highlight the importance of considering both individual- and state-level factors, as the interplay of such factors could hinder the successful implementation of cardiovascular risk reduction interventions.

The "dirty work" of last responders: Occupational stigma risk and protective factors.

Last responders constitute an occupational category that includes all those who are involved in the postmortem care of deceased persons and their families. The work of last responders is often considered "dirty work" and, as a result, stigmatized. Last responders are aware of this stigma, and stigma consciousness has been associated with negative health outcomes. Despite the wide acknowledgment of stigma among last responders, specific risk, or protective factors for experiencing stigma have not been investigated. This paper aims to identify determinants of stigma among last responders in the United States. The data for this study were obtained from a national cross-sectional survey of last responders. The survey included a measure of stigma and multiple sociodemographic characteristics. A hurdle model was used to assess the association between the characteristics of last responders and their perceived stigma. Respondents were predominantly male (55.1%), White non-Hispanic (90.2%), and employed full-time (96%). Seventy-seven percent reported having experienced at least one form of occupation-related stigma. There was no significant association between the experience of stigma and any socio-demographic variables. The experience of stigma is nearly ubiquitous among last responders->75% of last responders in the sample experienced at least one form of stigma. Another aspect of its ubiquitous nature is the lack of evidence that stigma was experienced differentially across sex, race/ethnicity, employment type, and length of years as a last responder. Interventions are needed to decrease stigma among last responders and to support last responders in managing the consequences of the stigma they experience.

Ignored and distressed: a cross-sectional study of the impact of COVID-19 on last responders.

BACKGROUND: Last responders constitute an occupational category that includes all those that are involved in the postmortem care of deceased persons and their families. Last responders are exposed to several categories of work-related stressors that affect their health and well-being. COVID-19 exacerbated these stressors. Research to understand the consequences of COVID-19 on the health and wellbeing of last responders is nascent. This study aimed to assess COVID-19 related stress, coping and wellbeing among last responders in the United States. METHODS: We conducted a national cross-sectional survey of last responders in July through September of 2020. The survey measured wellbeing, stress, coping, and stigma; COVID-19 experiences, and socio-demographics. A ridge regression model was fit for the outcome variables. RESULTS: Analysis was conducted on 366 respondents from 43 states. Respondents were male (55.4%), age 50 + (57.4%), and White non-Hispanic (90.3%); 54% reported moderate-high stress and 41% endorsed mild-severe anxiety. Seventy-seven percent had experienced at least one form of stigma related to their occupation. Variables associated with higher perceived stress and anxiety included gender (female), shorter length of employment, perceiving a higher impact from COVID-19 on everyday life, and increased perceived stigma. CONCLUSIONS: Last responders are a critical part of the health care system. Throughout this pandemic, last responders have been frequently ignored and not prioritized for protection and support. Interventions to support last responders cope with stress, and to decrease anxiety are urgently needed. There is also a critical need to challenge community stigma towards last responders.

Risk for Asymptomatic Household Transmission of Clostridioides difficile Infection Associated with Recently Hospitalized Family Members.

We evaluated whether hospitalized patients without diagnosed Clostridioides difficile infection (CDI) increased the risk for CDI among their family members after discharge. We used 2001-2017 US insurance claims data to compare monthly CDI incidence between persons in households with and without a family member hospitalized in the previous 60 days. CDI incidence among insurance enrollees exposed to a recently hospitalized family member was 73% greater than enrollees not exposed, and incidence increased with length of hospitalization among family members. We identified a dose-response relationship between total days of within-household hospitalization and CDI incidence rate ratio. Compared with persons whose family members were hospitalized <1 day, the incidence rate ratio increased from 1.30 (95% CI 1.19-1.41) for 1-3 days of hospitalization to 2.45 (95% CI 1.66-3.60) for >30 days of hospitalization. Asymptomatic C. difficile carriers discharged from hospitals could be a major source of community-associated CDI cases.

Evidence of within-facility patient-patient Clostridiodes difficile infection spread across diverse settings.

Previous studies have suggested that a hospital patient's risk of developing healthcare facility-onset (HCFO) Clostridioides difficile infections (CDIs) increases with the number of concurrent spatially proximate patients with CDI, termed CDI pressure. However, these studies were performed either in a single institution or in a single state with a very coarse measure of concurrence. We conducted a retrospective case-control study involving over 17.5 million inpatient visits across 700 hospitals in eight US states. We built a weighted, directed network connecting overlapping inpatient visits to measure facility-level CDI pressure. We then matched HCFO-CDIs with non-CDI controls on facility, comorbidities and demographics and performed a conditional logistic regression to determine the odds of developing HCFO-CDI given the number of coincident patient visits with CDI. On average, cases' visits coincided with 9.2 CDI cases, which for an individual with an average length of stay corresponded to an estimated 17.7% (95% CI 12.9-22.7%) increase in the odds of acquiring HCFO-CDI compared to an inpatient visit without concurrent CDI cases or fully isolated from both direct and indirect risks from concurrent CDI cases. These results suggest that, either directly or indirectly, hospital patients with CDI lead to CDIs in non-infected patients with temporally overlapping visits.

Risk for Clostridioides difficile Infection Among Hospitalized Patients Associated With Multiple Healthcare Exposures Prior to Admission.

BACKGROUND: Clostridioides difficile infection (CDI) is a common healthcare-associated infection and is often used as an indicator of hospital safety or quality. However, healthcare exposures occurring prior to hospitalization may increase risk for CDI. We conducted a case-control study comparing hospitalized patients with and without CDI to determine if healthcare exposures prior to hospitalization (ie, clinic visits, antibiotics, family members with CDI) were associated with increased risk for hospital-onset CDI, and how risk varied with time between exposure and hospitalization. METHODS: Records were collected from a large insurance-claims database from 2001 to 2017 for hospitalized adult patients. Prior healthcare exposures were identified using inpatient, outpatient, emergency department, and prescription drug claims; results were compared between various CDI case definitions. RESULTS: Hospitalized patients with CDI had significantly more frequent healthcare exposures prior to admission. Healthcare visits, antibiotic use, and family exposures were associated with greater likelihood of CDI during hospitalization. The degree of association diminished with time between exposure and hospitalization. Results were consistent across CDI case definitions. CONCLUSIONS: Many different prior healthcare exposures appear to increase risk for CDI presenting during hospitalization. Moreover, patients with CDI typically have multiple exposures prior to admission, confounding the ability to attribute cases to a particular stay.

Analysis of network interventions with an application to hospital-acquired infections.

Regional interventions to prevent the spread of hospital-acquired infections, vaccination campaigns, and information dissemination strategies are examples of treatment interventions applied to members of a network with the intent of effecting a network-wide change. In designing clinical trials or determining policy changes, it may not be cost effective or otherwise possible to treat all actors of a network. There is a notable lack of study designs and statistical frameworks with which to plan a network-wide intervention in this context and analyze the resulting data. This paper builds off of the network autocorrelation model in order to provide such a framework for a pre-post study design. We derive key quantitative measures of the network-wide treatment effect, exact formulas for power analyses of these measures, and extensions for the context in which the network is unknown. As the treatment assignation is part of the network-wide treatment, we provide methods for determining the assignation which optimizes the overall treatment effect over all members of the network subject to any arbitrary set of implementation costs and cost constraint. We implement these methods on Clostridioides difficile data for the state of California, where the hospitals are linked through patient sharing.

A qualitative assessment of the smoking policies and cessation activities at smaller workplaces.

BACKGROUND: To reduce the negative consequences of smoking, workplaces have adopted and implemented anti-smoking initiatives. Compared to large workplaces, less research exists about these initiatives at smaller workplaces, which are more likely to hire low-wage workers with higher rates of smoking. The purpose of this study was to describe and compare the smoking policies and smoking cessation activities at small (20-99 employees) and very small (< 20 employees) workplaces. METHODS: Thirty-two key informants coming from small and very small workplaces in Iowa completed qualitative telephone interviews. Data collection occurred between October 2016 and February 2017. Participants gave descriptions of the anti-smoking initiatives at their workplace. Additional interview topics included questions on enforcement, reasons for adoption, and barriers and facilitators to adoption and implementation. The data were analyzed using counts and content and thematic analysis. RESULTS: Workplace smoking policies were nearly universal (n = 31, 97%), and most workplaces (n = 21, 66%) offered activities to help employees quit smoking. Reasons for adoption included the Iowa Smokefree Air Act, to improve employee health, and organizational benefits (e.g., reduced insurance costs). Few challenges existed to adoption and implementation. Commonly cited facilitators included the Iowa Smokefree Air Act, no issues with compliance, and support from others. Compared to small workplaces, very small workplaces offered cessation activities less often and had fewer tobacco policy restrictions. CONCLUSIONS: This study showed well-established tobacco control efforts in small workplaces, but very small workplaces lagged behind. To reduce potential health disparities in smoking, future research and intervention efforts in tobacco control should focus on very small workplaces.

Calibration of the global physical activity questionnaire to Accelerometry measured physical activity and sedentary behavior.

BACKGROUND: Self-report questionnaires are a valuable method of physical activity measurement in public health research; however, accuracy is often lacking. The purpose of this study is to improve the validity of the Global Physical Activity Questionnaire by calibrating it to 7 days of accelerometer measured physical activity and sedentary behavior. METHODS: Participants (n = 108) wore an ActiGraph GT9X Link on their non-dominant wrist for 7 days. Following the accelerometer wear period, participants completed a telephone Global Physical Activity Questionnaire with a research assistant. Data were split into training and testing samples, and multivariable linear regression models built using functions of the GPAQ self-report data to predict ActiGraph measured physical activity and sedentary behavior. Models were evaluated with the testing sample and an independent validation sample (n = 120) using Mean Squared Prediction Errors. RESULTS: The prediction models utilized sedentary behavior, and moderate- and vigorous-intensity physical activity self-reported scores from the questionnaire, and participant age. Transformations of each variable, as well as break point analysis were considered. Prediction errors were reduced by 77.7-80.6% for sedentary behavior and 61.3-98.6% for physical activity by using the multivariable linear regression models over raw questionnaire scores. CONCLUSIONS: This research demonstrates the utility of calibrating self-report questionnaire data to objective measures to improve estimates of physical activity and sedentary behavior. It provides an understanding of the divide between objective and subjective measures, and provides a means to utilize the two methods as a unified measure.

The Seasonal Variability of Surgical Site Infections in Knee and Hip Arthroplasty.

BACKGROUND: Surgical site infections (SSIs) after total knee (TKA) and total hip (THA) arthroplasty are devastating to patients and costly to healthcare systems. The purpose of this study is to investigate the seasonality of TKA and THA SSIs at a national level. METHODS: All data were extracted from the National Readmission Database for 2013 and 2014. Patients were included if they had undergone TKA or THA. We modeled the odds of having a primary diagnosis of SSI as a function of discharge date by month, payer status, hospital size, and various patient co-morbidities. SSI status was defined as patients who were readmitted to the hospital with a primary diagnosis of SSI within 30 days of their arthroplasty procedure. RESULTS: There were 760,283 procedures (TKA 424,104, THA 336,179) in our sample. Our models indicate that SSI risk was highest for patients discharged from their surgery in June and lowest for December discharges. For TKA, the odds of a 30-day readmission for SSI were 30.5% higher at the peak compared to the nadir time (95% confidence interval [CI] 20-42). For THA, the seasonal increase in SSI was 19% (95% CI 9-30). Compared to Medicare, patients with Medicaid as the primary payer had a 49% higher odds of 30-day SSI after TKA (95% CI 32-68). CONCLUSION: SSIs following TKA and THA are seasonal peaking in summer months. Payer status was also a significant risk factor for SSIs. Future studies should investigate potential factors that could relate to the associations demonstrated in this study.

Warmer Weather as a Risk Factor for Cellulitis: A Population-based Investigation.

Background: The incidence of cellulitis is highly seasonal and this seasonality may be explained by changes in the weather, specifically, temperature. Methods: Using data from the Nationwide Inpatient Sample (years 1998 to 2011), we identified the geographic location for 773719 admissions with the primary diagnosis (ICD-9-CM code) of cellulitis and abscess of finger and toe (681.XX) and other cellulitis and abscess (682.XX). Next, we used data from the National Climatic Data Center to estimate the monthly average temperature for each of these different locations. We modeled the odds of an admission having a primary diagnosis of cellulitis as a function of demographics, payer, location, patient severity, admission month, year, and the average temperature in the month of admission. Results: We found that the odds of an admission with a primary diagnosis of cellulitis increase with higher temperatures in a dose-response fashion. For example, relative to a cold February with average temperatures under 40° F, an admission in a hot July with an average temperature exceeding 90°F has 66.63% higher odds of being diagnosed with cellulitis (95% confidence interval [CI]: [61.2, 72.3]). After controlling for temperature, the estimated amplitude of seasonality of cellulitis decreased by approximately 71%. Conclusion: At a population level, admissions to the hospital for cellulitis risk are strongly associated with warmer weather.

Weather-Dependent Risk for Legionnaires' Disease, United States.

Using the Nationwide Inpatient Sample and US weather data, we estimated the probability of community-acquired pneumonia (CAP) being diagnosed as Legionnaires' disease (LD). LD risk increases when weather is warm and humid. With warm weather, we found a dose-response relationship between relative humidity and the odds for LD. When the mean temperature was 60°-80°F with high humidity (>80.0%), the odds for CAP being diagnosed with LD were 3.1 times higher than with lower levels of humidity (<50.0%). Thus, in some regions (e.g., the Southwest), LD is rarely the cause of hospitalizations. In other regions and seasons (e.g., the mid-Atlantic in summer), LD is much more common. Thus, suspicion for LD should increase when weather is warm and humid. However, when weather is cold, dry, or extremely hot, empirically treating all CAP patients for LD might contribute to excessive antimicrobial drug use at a population level.

Hospitalizations among family members increase the risk of MRSA infection in a household.

OBJECTIVE: Estimate the risk for household transmission of Methicillin-Resistant Staphylococcus aureus (MRSA) following exposure to infected family members or family members recently discharged from a hospital. DESIGN: Analysis of monthly MRSA incidence from longitudinal insurance claims using the Merative MarketScan Commercial and Medicare (2001-2021) databases. SETTING: Visits to inpatient, emergency department, and outpatient settings. PATIENTS: Households with ≥2 family members enrolled in the same insurance plan for the entire month. METHODS: We estimated a monthly incidence model, where enrollees were binned into monthly enrollment strata defined by demographic, patient, and exposure characteristics. Monthly incidence within each stratum was computed, and a regression analysis was used to estimate the incidence rate ratio (IRR) associated with household exposures of interest while accounting for potential confounding factors. RESULTS: A total of 157,944,708 enrollees were included and 424,512 cases of MRSA were identified. Across all included enrollees, exposure to a family member with MRSA in the prior 30 days was associated with significantly increased risk of infection (IRR: 71.03 [95% CI, 67.73-74.50]). After removing enrollees who were hospitalized or exposed to a family member with MRSA, exposure to a family member who was recently discharged from the hospital was associated with increased risk of infection (IRR: 1.44 [95% CI, 1.39-1.49]) and the risk of infection increased with the duration of the family member's hospital stay (P value < .001). CONCLUSIONS: Exposure to a recently hospitalized and discharged family member increased the risk of MRSA infection in a household even when the hospitalized family member was not diagnosed with MRSA.

Comparing multiple infection control measures in a nursing home setting: a simulation study.

OBJECTIVE: Compare the effectiveness of multiple mitigation measures designed to protect nursing home residents from infectious disease outbreaks. DESIGN: Agent-based simulation study. SETTING: Simulation environment of a small nursing home. METHODS: We collected temporally detailed and spatially fine-grained location information from nursing home healthcare workers (HCWs) using sensor motes. We used these data to power an agent-based simulation of a COVID-19 outbreak using realistic time-varying estimates of infectivity and diagnostic sensitivity. Under varying community prevalence and transmissibility, we compared the mitigating effects of (i) regular screening and isolation, (ii) inter-resident contact restrictions, (iii) reduced HCW presenteeism, and (iv) modified HCW scheduling. RESULTS: Across all configurations tested, screening every other day and isolating positive cases decreased the attack rate by an average of 27% to 0.501 on average, while contact restrictions decreased the attack rate by an average of 35%, resulting in an attack rate of only 0.240, approximately half that of screening/isolation. Combining both interventions impressively produced an attack rate of only 0.029. Halving the observed presenteeism rate led to an 18% decrease in the attack rate, but if combined with screening every 6 days, the effect of reducing presenteeism was negligible. Altering work schedules had negligible effects on the attack rate. CONCLUSIONS: Universal contact restrictions are highly effective for protecting vulnerable nursing home residents, yet adversely affect physical and mental health. In high transmission and/or high community prevalence situations, restricting inter-resident contact to groups of 4 was effective and made highly effective when paired with weekly testing.

Comparison of Different Antibiotics and the Risk for Community-Associated Clostridioides difficile Infection: A Case-Control Study.

Background: Antibiotics are the greatest risk factor for Clostridioides difficile infection (CDI). Risk for CDI varies across antibiotic types and classes. Optimal prescribing and stewardship recommendations require comparisons of risk across antibiotics. However, many prior studies rely on aggregated antibiotic categories or are underpowered to detect significant differences across antibiotic types. Using a large database of real-world data, we evaluate community-associated CDI risk across individual antibiotic types. Methods: We conducted a matched case-control study using a large database of insurance claims capturing longitudinal health care encounters and medications. Case patients with community-associated CDI were matched to 5 control patients by age, sex, and enrollment period. Antibiotics prescribed within 30 days before the CDI diagnosis along with other risk factors, including comorbidities, health care exposures, and gastric acid suppression were considered. Conditional logistic regression and a Bayesian analysis were used to compare risk across individual antibiotics. A sensitivity analysis of antibiotic exposure windows between 30 and 180 days was conducted. Results: We identified 159 404 cases and 797 020 controls. Antibiotics with the greatest risk for CDI included clindamycin and later-generation cephalosporins, and those with the lowest risk included minocycline and doxycycline. We were able to differentiate and order individual antibiotics in terms of their relative level of associated risk for CDI. Risk estimates varied considerably with different exposure windows considered. Conclusions: We found wide variation in CDI risk within and between classes of antibiotics. These findings ordering the level of associated risk across antibiotics can help inform tradeoffs in antibiotic prescribing decisions and stewardship efforts.

Predicting use of a gait-stabilizing device using a Wii Balance Board.

Gait-stabilizing devices (GSDs) are effective at preventing falls, but people are often reluctant to use them until after experiencing a fall. Inexpensive, convenient, and effective methods for predicting which patients need GSDs could help improve adoption. The purpose of this study was to determine if a Wii Balance Board (WBB) can be used to determine whether or not patients use a GSD. We prospectively recruited participants ages 70-100, some who used GSDs and some who did not. Participants first answered questions from the Modified Vulnerable Elders Survey, and then completed a grip-strength test using a handgrip dynamometer. Finally, they were asked to complete a series of four 30-second balance tests on a WBB in random order: (1) eyes open, feet apart; (2) eyes open, feet together; (3) eyes closed, feet apart; and (4) eyes closed, feet together. The four-test series was repeated a second time in the same random order. The resulting data, represented as 25 features extracted from the questionnaires and the grip test, and data from the eight balance tests, were used to predict a subject's GSD use using generalized functional linear models based on the Bernoulli distribution. 268 participants were consented; 62 were missing data elements and were removed from analysis; 109 were not GSD users and 97 were GSD users. The use of velocity and acceleration information from the WBB improved upon predictions based solely on grip strength, demographic, and survey variables. The WBB is a convenient, inexpensive, and easy-to-use device that can be used to recommend whether or not patients should be using a GSD.

Identifying the Social Determinants of Treated Hypertension in New and Established Latino Destination States.

Little is known about the influence of social and environmental contexts on Latino hypertension-related disparities. This study examined the influence of social determinants of cardiovascular health on medically treated hypertension, contrasting established vs. new Latino destination states. Logistic regression models were fitted to analyze 2017 Behavioral Risk Factors Surveillance Survey data from 8,999 Latinos. Overall, 70.4% indicated having treated hypertension. History of diabetes (OR = 2.60) and access to healthcare (OR = 2.38) were associated with treated hypertension, regardless of destination state. In established destinations, Latinos who graduated high school (OR = 1.19) or attended college (OR = 1.32) had higher odds of treated hypertension; whereas those who completed college were less likely to have treated hypertension (OR = 0.80). In contrast, in both new and non-destination states, the odds of treated hypertension were consistently lower across levels of educational attainment. Results highlight the need for cardiovascular-risk reduction interventions to incorporate the social and environmental context in the development process.

Protocol for the PATHOME study: a cohort study on urban societal development and the ecology of enteric disease transmission among infants, domestic animals and the environment.

INTRODUCTION: Global morbidity from enteric infections and diarrhoea remains high in children in low-income and middle-income countries, despite significant investment over recent decades in health systems and water and sanitation infrastructure. Other types of societal development may be required to reduce disease burden. Ecological research on the influence of household and neighbourhood societal development on pathogen transmission dynamics between humans, animals and the environment could identify more effective strategies for preventing enteric infections. METHODS AND ANALYSIS: The 'enteric pathome'-that is, the communities of viral, bacterial and parasitic pathogens transmitted from human and animal faeces through the environment is taxonomically complex in high burden settings. This integrated cohort-exposure assessment study leverages natural socioeconomic spectrums of development to study how pathome complexity is influenced by household and neighbourhood infrastructure and hygiene conditions. We are enrolling under 12-month-old children in low-income and middle-income neighbourhoods of two Kenyan cities (Nairobi and Kisumu) into a 'short-cohort' study involving repeat testing of child faeces for enteric pathogens. A mid-study exposure assessment documenting infrastructural, behavioural, spatial, climate, environmental and zoonotic factors characterises pathogen exposure pathways in household and neighbourhood settings. These data will be used to inform and validate statistical and agent-based models (ABM) that identify individual or combined intervention strategies for reducing multipathogen transmission between humans, animals and environment in urban Kenya. ETHICS AND DISSEMINATION: The protocols for human subjects' research were approved by Institutional Review Boards at the University of Iowa (ID-202004606) and AMREF Health Africa (ID-ESRC P887/2020), and a national permit was obtained from the Kenya National Commission for Science Technology and Innovation (ID# P/21/8441). The study was registered on Clinicaltrials.gov (Identifier: NCT05322655) and is in pre-results stage. Protocols for research on animals were approved by the University of Iowa Animal Care and Use Committee (ID 0042302).

Network-Informed Constrained Divisive Pooled Testing Assignments.

Frequent universal testing in a finite population is an effective approach to preventing large infectious disease outbreaks. Yet when the target group has many constituents, this strategy can be cost prohibitive. One approach to alleviate the resource burden is to group multiple individual tests into one unit in order to determine if further tests at the individual level are necessary. This approach, referred to as a group testing or pooled testing, has received much attention in finding the minimum cost pooling strategy. Existing approaches, however, assume either independence or very simple dependence structures between individuals. This assumption ignores the fact that in the context of infectious diseases there is an underlying transmission network that connects individuals. We develop a constrained divisive hierarchical clustering algorithm that assigns individuals to pools based on the contact patterns between individuals. In a simulation study based on real networks, we show the benefits of using our proposed approach compared to random assignments even when the network is imperfectly measured and there is a high degree of missingness in the data.