Potential Impact of a Diagnostic Test for Detecting Prepatent Guinea Worm Infections in Dogs.

Chad has seen a considerable reduction in cases of Guinea worm disease (or dracunculiasis) in domestic dogs in recent years. Tethering of dogs and application of Abate® larvicide to water sources appear to have contributed to this progress, but with 767 reported dog cases in 2021, accelerating elimination of the disease in Chad may require additional tools. We investigate the potential benefits of a hypothetical diagnostic test that could be capable of detecting prepatent infections in dogs. We adapt an agent-based simulation model for forecasting the impact of interventions on guinea worm disease in dogs to examine the interaction of multiple test factors including test accuracy, when the test can detect infection, dog selection, and dog-owner compliance with tethering recommendations. We find that a diagnostic test could be successful if used in conjunction with existing interventions, and elimination can be achieved within 2 years with 80% or higher test sensitivity, 90% or higher specificity, systematic testing of each dog twice per year, and more than 90% long-term tethering compliance when a dog tests positive or a worm is emerging. Because of the long incubation period of Guinea worm disease (10-14 months) and the fact that no treatment exists, the benefits of the test rely on the testing rollout and response of dog owners. If the test could estimate the timing of worm emergence, long-term tethering could be eliminated and infected dogs could be tethered only when the worms are expected, minimizing the related resources (human and financial) to support the intervention.

Factors associated with vaccine coverage improvements in Senegal between 2005 and 2019: a quantitative retrospective analysis.

OBJECTIVE: Senegal has demonstrated catalytic improvements in national coverage rates for early childhood vaccination, despite lower development assistance for childhood vaccines in Senegal compared with other low-income and lower-middle income countries. Understanding factors associated with historical changes in childhood vaccine coverage in Senegal, as well as heterogeneities across its 14 regions, can highlight effective practices that might be adapted to improve vaccine coverage elsewhere. DESIGN: Childhood vaccination coverage rates, demographic information and health system characteristics were identified from Senegal's Demographic and Health Surveys (DHS) and Senegal national reports for years 2005-2019. Multivariate logistic and linear regression analyses were performed to determine statistical associations of demographic and health system characteristics with respect to childhood vaccination coverage rates. SETTING: The 14 administrative regions of Senegal were chosen for analysis. PARTICIPANTS: DHS women's survey respondents with living children aged 12-23 months for survey years 2005-2019. OUTCOME MEASURES: Immunisation with the third dose of the diphtheria-tetanus-pertussis vaccine (DTP3), widely used as a proxy for estimating immunisation coverage levels and the retention of children in the vaccine programme. RESULTS: Factors associated with childhood vaccination coverage include urban residence (ß=0.61, p=0.0157), female literacy (ß=1.11, p=0.0007), skilled prenatal care (ß=1.80, p<0.0001) and self-reported ease of access to care when sick, considering travel distance to a healthcare facility (ß=-0.70, p=0.0009) and concerns over travelling alone (ß=-1.08, p<0.0001). Higher coverage with less variability over time was reported in urban areas near the capital and the coast (p=0.076), with increased coverage in recent years in more rural and landlocked areas. CONCLUSIONS: Childhood vaccination was more likely among children whose mothers had higher literacy, received skilled prenatal care and had perceived ease of access to care when sick. Overall, vaccination coverage is high in Senegal and disparities in coverage between regions have decreased significantly in recent years.

Evaluating the Effectiveness of Potential Interventions for Guinea Worm Disease in Dogs in Chad Using Simulations.

Guinea worm (GW) disease (or dracunculiasis) is currently transmitted among dogs in Chad, which presents risks for the human population. We studied how interventions implemented at different levels might reduce the spread of GW disease (geographically and over time) and what levels of interventions might accelerate elimination. We built a multiple-water-source agent-based simulation model to analyze the disease transmission among dogs in Chad, as well as in geographic district clusters, and validated it using local infection data. We considered two interventions: 1) tethering, where infected dogs are kept on a leash during periods of infectivity, and 2) Abate®, under which the water source is treated to reduce infectivity. Our results showed that elimination (0 dog infections) is most likely achieved within 5 years with extremely high levels of tethering (95%) and Abate (90%), when intervention levels are uniform across district clusters. We used an optimization model to determine an improved strategy, with intervention levels which minimize the number of dogs newly infected in the 6th year, under limitations on intervention levels across clusters; the number of dogs infected after 5 years of intervention could be reduced by approximately 220 dogs with an optimized strategy. Finally, we presented strategies that consider fairness based on intervention resource levels and outcomes. Increased tethering and Abate resources above historical levels are needed to achieve the target of GW disease elimination; optimization methods can inform how best to target limited resources and reach elimination faster.

A mathematical model to describe survival among liver recipients from deceased donors with risk of transmitting infectious encephalitis pathogens.

BACKGROUND: Between 2002 and 2013, the organs of 13 deceased donors with infectious encephalitis were transplanted, causing infections in 23 recipients. As a consequence, organs from donors showing symptoms of encephalitis (increased probability of infectious encephalitis (IPIE) organs) might be declined. We had previously characterized the risk of IPIE organs using data available to most transplant teams and not requiring special diagnostic tests. If the probability of infection is low, the benefits of a transplant from a donor with suspected infectious encephalitis might outweigh the risk and could be lifesaving for some transplant candidates. METHODS: Using organ transplant data and Cox Proportional Hazards models, we determined liver donor and recipient characteristics predictive of post-transplant or waitlist survival and generated 5-year survival probability curves. We also calculated expected waiting times for an organ offer based on transplant candidate characteristics. Using a limited set of actual cases of infectious encephalitis transmission via transplant, we estimated post-transplant survival curves given an organ from an IPIE donor. RESULTS: 54% (1256) of patients registered from 2002-2006 who died or were removed from the waiting list because of deteriorated condition within 1 year could have had an at least marginal estimated benefit by accepting an IPIE liver with some probability of infection, with the odds increasing to 86% of patients if the probability of infection was low (5% or less). Additionally, 54% (1252) were removed from the waiting list prior to their estimated waiting time for a non-IPIE liver and could have benefited from an IPIE liver. CONCLUSION: Improved allocation and utilization of IPIE livers could be achieved by evaluating the patient-specific trade-offs between (a) accepting an IPIE liver and (b) remaining on the waitlist and accepting a non-IPIE liver after the estimated waiting time.

Assessment of risk for transplant-transmissible infectious encephalitis among deceased organ donors.

BACKGROUND: There were 13 documented clusters of infectious encephalitis transmission via organ transplant from deceased donors to recipients during 2002-2013. Hence, organs from donors diagnosed with encephalitis are often declined because of concerns about the possibility of infection, given that there is no quick and simple test to detect causes of infectious encephalitis. METHODS: We constructed a database containing cases of infectious and non-infectious encephalitis. Using statistical imputation, cross-validation, and regression techniques, we determined deceased organ donor characteristics, including demographics, signs, symptoms, physical exam, and laboratory findings, predictive of infectious vs non-infectious encephalitis, and developed a calculator which assesses the risk of infection. RESULTS: Using up to 12 predictive patient characteristics (with a minimum of 3, depending on what information is available), the calculator provides the probability that a donor may have infectious vs non-infectious encephalitis, improving the prediction accuracy over current practices. These characteristics include gender, fever, immunocompromised state (other than HIV), cerebrospinal fluid elevation, altered mental status, psychiatric features, cranial nerve abnormality, meningeal signs, focal motor weakness, Babinski's sign, movement disorder, and sensory abnormalities. CONCLUSION: In the absence of definitive diagnostic testing in a potential organ donor, infectious encephalitis can be predicted with a risk score. The risk calculator presented in this paper represents a prototype, establishing a framework that can be expanded to other infectious diseases transmissible through solid organ transplantation.

Automated medical resident rotation and shift scheduling to ensure quality resident education and patient care.

At academic teaching hospitals around the country, the majority of clinical care is provided by resident physicians. During their training, medical residents often rotate through various hospitals and/or medical services to maximize their education. Depending on the size of the training program, manually constructing such a rotation schedule can be cumbersome and time consuming. Further, rules governing allowable duty hours for residents have grown more restrictive in recent years (ACGME 2011), making day-to-day shift scheduling of residents more difficult (Connors et al., J Thorac Cardiovasc Surg 137:710-713, 2009; McCoy et al., May Clin Proc 86(3):192, 2011; Willis et al., J Surg Edu 66(4):216-221, 2009). These rules limit lengths of duty periods, allowable duty hours in a week, and rest periods, to name a few. In this paper, we present two integer programming models (IPs) with the goals of (1) creating feasible assignments of residents to rotations over a one-year period, and (2) constructing night and weekend call-shift schedules for the individual rotations. These models capture various duty-hour rules and constraints, provide the ability to test multiple what-if scenarios, and largely automate the process of schedule generation, solving these scheduling problems more effectively and efficiently compared to manual methods. Applying our models on data from a surgical residency program, we highlight the infeasibilities created by increased duty-hour restrictions placed on residents in conjunction with current scheduling paradigms.

Optimized oral cholera vaccine distribution strategies to minimize disease incidence: A mixed integer programming model and analysis of a Bangladesh scenario.

In addition to improved sanitation, hygiene, and better access to safe water, oral cholera vaccines can help to control the spread of cholera in the short term. However, there is currently no systematic method for determining the best allocation of oral cholera vaccines to minimize disease incidence in a population where the disease is endemic and resources are limited. We present a mathematical model for optimally allocating vaccines in a region under varying levels of demographic and incidence data availability. The model addresses the questions of where, when, and how many doses of vaccines to send. Considering vaccine efficacies (which may vary based on age and the number of years since vaccination), we analyze distribution strategies which allocate vaccines over multiple years. Results indicate that, given appropriate surveillance data, targeting age groups and regions with the highest disease incidence should be the first priority, followed by other groups primarily in order of disease incidence, as this approach is the most life-saving and cost-effective. A lack of detailed incidence data results in distribution strategies which are not cost-effective and can lead to thousands more deaths from the disease. The mathematical model allows for what-if analysis for various vaccine distribution strategies by providing the ability to easily vary parameters such as numbers and sizes of regions and age groups, risk levels, vaccine price, vaccine efficacy, production capacity and budget.

Development of a handoff continuity score to improve pediatric ICU physician schedule design for enhanced physician and patient continuity.

INTRODUCTION: Few studies investigate the benefits of familiarity or continuity during physician-to-physician handoff of inpatients. Factors such as how recently physicians (MDs) have worked and successive days caring for patients increase continuity, and thus could lead to enhanced handoff efficiency. Evaluating the efficacy of MD scheduling to enhance continuity is currently subjective. METHODS: An MD group consisting of 9 attending physicians and 7 fellows redesigned its pediatric intensive care unit (PICU) coverage schedule with the goal of enhancing continuity of care. The attending PICU MDs were formally surveyed to rate the impact of the schedule change on continuity and efficiency (5 point Likert scale: 1 = worse, 3 = no change, 5 = better). A Handoff Continuity Score (HCS) was developed and used to analyze the 30-bed PICU MD schedule for continuity and handoff efficiency. MD service and call schedules were evaluated for 6-month periods before and after the schedule redesign. The HCS for each schedule was calculated by considering every shift change, or handoff, in the scheduling horizon, and assigning scores to oncoming physicians based on previous days worked. Specifically, for each handoff, each oncoming MD receives a score between 0 and 1, calculated as the summation of a series of 'familiarity factors', one for each recent day worked. The scores for all oncoming MDs are averaged to determine the score for that specific handoff, and the HCS is the average of all handoff scores. The HCS was incorporated into an integer programming (IP) model for scheduling MDs to maximize continuity. A z-test was used to assess the significance of improvement in the HCS. RESULTS: The HCS before and after redesign was 0.57 and 0.68, respectively (19% increase, p < 0.01). Mean MD rating was 4.22 ± 0.56 for continuity, and 4.00 ± 0.65 for efficiency. With the goal of further improving the HCS and (partly) automating and streamlining the scheduling process, the IP was developed to populate physician service and night-call schedules while conforming to scheduling constraints; IP-generated schedules improved the HCS to 0.79 (39% increase). CONCLUSIONS: The increased HCS was associated with the MD qualitative assessment of enhanced continuity and efficiency after implanting a schedule change. The IP identified the potential for additional scheduling improvements.

A framework for assessing patient crossover and health information exchange value.

OBJECTIVE: To evaluate the benefit of a health information exchange (HIE) between hospitals, we examine the rate of crossover among neurosurgical inpatients treated at Emory University Hospital (EUH) and Grady Memorial Hospital (GMH) in Atlanta, Georgia. To inform decisions regarding investment in HIE, we develop a methodology analyzing crossover behavior for application to larger more general patient populations. DESIGN: Using neurosurgery inpatient visit data from EUH and GMH, unique patients who visited both hospitals were identified through classification by name and age at time of visit. The frequency of flow patterns, including time between visits, and the statistical significance of crossover rates for patients with particular diagnoses were determined. MEASUREMENTS: The time between visits, flow patterns, and proportion of patients exhibiting crossover behavior were calculated for the total population studied as well as subpopulations. RESULTS: 5.25% of patients having multiple visits over the study period visited the neurosurgical departments at both hospitals. 77% of crossover patients visited the level 1 trauma center (GMH) before visiting EUH. LIMITATIONS: The true patient crossover may be under-estimated because the study population only consists of neurosurgical inpatients at EUH and GMH. CONCLUSION: We demonstrate that detailed analysis of crossover behavior provides a deeper understanding of the potential value of HIE.