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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

Leveraging network structure to improve pooled testing efficiency.

Screening is a powerful tool for infection control, allowing for infectious individuals, whether they be symptomatic or asymptomatic, to be identified and isolated. The resource burden of regular and comprehensive screening can often be prohibitive, however. One such measure to address this is pooled testing, whereby groups of individuals are each given a composite test; should a group receive a positive diagnostic test result, those comprising the group are then tested individually. Infectious disease is spread through a transmission network, and this paper shows how assigning individuals to pools based on this underlying network can improve the efficiency of the pooled testing strategy, thereby reducing the resource burden. We designed a simulated annealing algorithm to improve the pooled testing efficiency as measured by the ratio of the expected number of correct classifications to the expected number of tests performed. We then evaluated our approach using an agent-based model designed to simulate the spread of SARS-CoV-2 in a school setting. Our results suggest that our approach can decrease the number of tests required to regularly screen the student body, and that these reductions are quite robust to assigning pools based on partially observed or noisy versions of the network.

Predicting an optimal composite outcome variable for Huntington's disease clinical trials.

While there is no known cure for Huntington's disease (HD), there are early-phase clinical trials aimed at altering disease progression patterns. There is, however, no obvious single outcome for these trials to evaluate treatment efficacy. Currently used outcomes are, while reasonable, not optimal in any sense. In this paper we derive a method for constructing a composite variable via a linear combination of clinical measures. Our composite variable optimizes the signal-to-noise ratio (SNR) within the context of a longitudinal study design. We also demonstrate how to induce sparsity using a soft-approximation of an L 1 penalty on the coefficients of the composite variable. We applied our method to data from the TRACK-HD study, a longitudinal study aimed at establishing good outcome measures for HD, and found that compared to the existing composite measurement our composite variable provides a larger SNR and allows clinical trials with smaller sample sizes to achieve equivalent power.

Milk Product Safety and Household Food Hygiene Influence Bacterial Contamination of Infant Food in Peri-Urban Kenya.

BACKGROUND: Milk is a common infant food in peri-urban Kenya that can transmit diarrhea-causing enteric pathogens. Little is known about how contamination of milk at point of purchase and household handling of milk-based infant foods contribute to infant exposure to enteric pathogens. OBJECTIVE: To compare the prevalence and concentrations of bacterial indicator organisms and enteric pathogens in unpackaged, fresh pasteurized, and ultra-high temperature (UHT) treated milk at purchase and assess the influence of the type of milk used to prepare infant food on contamination of this food. METHODS: Paired samples of purchased milk and infant food prepared with this milk were obtained from 188 households in low-income neighborhoods in Kisumu, Kenya. Samples were cultured on selective media to isolate Salmonella enterica, Shigella spp., Klebsiella aerogenes, Proteus spp., and Escherichia coli, with pathogens validated by PCR. Probability of detection of these bacteria was compared by milk product treatment and packaging method, and between milk at point of purchase vs. food at point of infant consumption. RESULTS: Unpackaged milk was most contaminated at point of purchase, but bacterial contamination was also present in pasteurized and UHT milk at purchase. Presence of bacteria in UHT and fresh pasteurized milk at purchase predicted presence of the same bacteria type in infant food. Prevalence of bacterial contamination and concentration level for bacterial indicators generally increased between point of purchase and consumption in UHT and fresh pasteurized milk-based food but decreased in unpackaged milk-based food. Prevalence of the four fecal bacteria were similar in infant foods prepared with each type of milk. CONCLUSION: Both pre-market contamination and post-purchase handling influence the likelihood of infants ingesting foods contaminated by diarrheal pathogens.

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.

Simulation-free estimation of an individual-based SEIR model for evaluating nonpharmaceutical interventions with an application to COVID-19 in the District of Columbia.

The ongoing COVID-19 pandemic has overwhelmingly demonstrated the need to accurately evaluate the effects of implementing new or altering existing nonpharmaceutical interventions. Since these interventions applied at the societal level cannot be evaluated through traditional experimental means, public health officials and other decision makers must rely on statistical and mathematical epidemiological models. Nonpharmaceutical interventions are typically focused on contacts between members of a population, and yet most epidemiological models rely on homogeneous mixing which has repeatedly been shown to be an unrealistic representation of contact patterns. An alternative approach is individual based models (IBMs), but these are often time intensive and computationally expensive to implement, requiring a high degree of expertise and computational resources. More often, decision makers need to know the effects of potential public policy decisions in a very short time window using limited resources. This paper presents a computation algorithm for an IBM designed to evaluate nonpharmaceutical interventions. By utilizing recursive relationships, our method can quickly compute the expected epidemiological outcomes even for large populations based on any arbitrary contact network. We utilize our methods to evaluate the effects of various mitigation measures in the District of Columbia, USA, at various times and to various degrees. Rcode for our method is provided in the supplementry material, thereby allowing others to utilize our approach for other regions.

A pharmacist intervention for monitoring and treating hypertension using bidirectional texting: PharmText BP.

BACKGROUND: New approaches are needed to better monitor blood pressure (BP) between physician visits, especially for patients in rural areas or for those who lack transportation. We have developed a custom-built bi-directional texting platform for home BP measurements that can then be managed by clinical pharmacists located remotely. The purpose of this study is to evaluate whether the BP texting approach combined with a pharmacist-based intervention improves BP management and to determine if the approach is cost effective. METHODS: This study is a randomized, prospective trial in four primary care offices that serve patients in rural areas. Subjects will receive standardized research BP measurements at baseline, 6 and 12 months. The primary outcome will be differences between the intervention and control group in mean systolic BP at 12 months. Secondary outcomes will include systolic BP at 6 months; diastolic BP at 6 and 12 months, number of medication changes and costs. CONCLUSIONS: This study plans to enroll subjects through 2022, follow-up will be completed in 2023 and results will be available in 2024. This study will provide information on whether a combined approach using texting of home BP values and a pharmacist-based telehealth services can improve BP control.

Association of Household Exposure to Primary Clostridioides difficile Infection With Secondary Infection in Family Members.

Importance: Clostridioides difficile infection (CDI) is a common hospital-acquired infection. Whether family members are more likely to experience a CDI following CDI in another separate family member remains to be studied. Objective: To determine the incidence of potential family transmission of CDI. Design, Setting, and Participants: In this case-control study comparing the incidence of CDI among individuals with prior exposure to a family member with CDI to those without prior family exposure, individuals were binned into monthly enrollment strata based on exposure status (eg, family exposure) and confounding factors (eg, age, prior antibiotic use). Data were derived from population-based, longitudinal commercial insurance claims from the Truven Marketscan Commercial Claims and Encounters and Medicare Supplemental databases from 2001 to 2017. Households with at least 2 family members continuously enrolled for at least 1 month were eligible. CDI incidence was computed within each stratum. A regression model was used to compare incidence of CDI while controlling for possible confounding characteristics. Exposures: Index CDI cases were identified using inpatient and outpatient diagnosis codes. Exposure risks 60 days prior to infection included CDI diagnosed in another family member, prior hospitalization, and antibiotic use. Main Outcomes and Measures: The primary outcome was the incidence of CDI in a given monthly enrollment stratum. Separate analyses were considered for CDI diagnosed in outpatient or hospital settings. Results: A total of 224 818 cases of CDI, representing 194 424 enrollees (55.9% female; mean [SD] age, 52.8 [22.2] years) occurred in families with at least 2 enrollees. Of these, 1074 CDI events (4.8%) occurred following CDI diagnosis in a separate family member. Prior family exposure was significantly associated with increased incidence of CDI, with an incidence rate ratio (IRR) of 12.47 (95% CI, 8.86-16.97); this prior family exposure represented the factor with the second highest IRR behind hospital exposure (IRR, 16.18 [95% CI, 15.31-17.10]). For community-onset CDI cases without prior hospitalization, the IRR for family exposure was 21.74 (95% CI, 15.12-30.01). Age (IRR, 9.90 [95% CI, 8.92-10.98] for ages ≥65 years compared with ages 0-17 years), antibiotic use (IRR, 3.73 [95% CI, 3.41-4.08] for low-risk and 14.26 [95% CI, 13.27-15.31] for high-risk antibiotics compared with no antibiotics), and female sex (IRR, 1.44 [95% CI, 1.36-1.53]) were also positively associated with incidence. Conclusions and Relevance: This study found that individuals with family exposure may be at significantly greater risk for acquiring CDI, which highlights the importance of the shared environment in the transmission and acquisition of C difficile.

Spatiotemporal clustering of in-hospital Clostridioides difficile infection.

OBJECTIVE: To determine whether Clostridioides difficile infection (CDI) exhibits spatiotemporal interaction and clustering. DESIGN: Retrospective observational study. SETTING: The University of Iowa Hospitals and Clinics. PATIENTS: This study included 1,963 CDI cases, January 2005 through December 2011. METHODS: We extracted location and time information for each case and ran the Knox, Mantel, and mean and maximum component size tests for time thresholds (T = 7, 14, and 21 days) and distance thresholds (D = 2, 3, 4, and 5 units; 1 unit = 5-6 m). All tests were implemented using Monte Carlo simulations, and random CDI cases were constructed by randomly permuting times of CDI cases 20,000 times. As a counterfactual, we repeated all tests on 790 aspiration pneumonia cases because aspiration pneumonia is a complication without environmental factors. RESULTS: Results from the Knox test and mean component size test rejected the null hypothesis of no spatiotemporal interaction (P < .0001), for all values of T and D. Results from the Mantel test also rejected the hypothesis of no spatiotemporal interaction (P < .0003). The same tests showed no such effects for aspiration pneumonia. Our results from the maximum component size tests showed similar trends, but they were not consistently significant, possibly because CDI outbreaks attributable to the environment were relatively small. CONCLUSION: Our results clearly show spatiotemporal interaction and clustering among CDI cases and none whatsoever for aspiration pneumonia cases. These results strongly suggest that environmental factors play a role in the onset of some CDI cases. However, our results are not inconsistent with the possibility that many genetically unrelated CDI cases occurred during the study period.