Embracing dynamic public health policy impacts in infectious diseases responses: leveraging implementation science to improve practice

RationaleThe host-pathogen relationship is inherently dynamic and constantly evolving. Applying an implementation science lens to policy evaluation suggests that policy impacts are variable depending upon key implementation outcomes (feasibility, acceptability, appropriateness costs) and conditions and contexts.COVID-19 case studyExperiences with non-pharmaceutical interventions (NPIs) including masking, testing, and social distancing/business and school closures during the COVID-19 pandemic response highlight the importance of considering public health policy impacts through an implementation science lens of constantly evolving contexts, conditions, evidence, and public perceptions. As implementation outcomes (feasibility, acceptability) changed, the effectiveness of these interventions changed thereby altering public health policy impact. Sustainment of behavioral change may be a key factor determining the duration of effectiveness and ultimate impact of pandemic policy recommendations, particularly for interventions that require ongoing compliance at the level of the individual.Practical framework for assessing and evaluating pandemic policyUpdating public health policy recommendations as more data and alternative interventions become available is the evidence-based policy approach and grounded in principles of implementation science and dynamic sustainability. Achieving the ideal of real-time policy updates requires improvements in public health data collection and analysis infrastructure and a shift in public health messaging to incorporate uncertainty and the necessity of ongoing changes. In this review, the Dynamic Infectious Diseases Public Health Response Framework is presented as a model with a practical tool for iteratively incorporating implementation outcomes into public health policy design with the aim of sustaining benefits and identifying when policies are no longer functioning as intended and need to be adapted or de-implemented.Conclusions and implicationsReal-time decision making requires sensitivity to conditions on the ground and adaptation of interventions at all levels. When asking about the public health effectiveness and impact of non-pharmaceutical interventions, the focus should be on when, how, and for how long they can achieve public health impact. In the future, rather than focusing on models of public health intervention effectiveness that assume static impacts, policy impacts should be considered as dynamic with ongoing re-evaluation as conditions change to meet the ongoing needs of the ultimate end-user of the intervention: the public

Pandemic scientific data sharing recommendations: examining and re-imagining pre-print servers after the end of the world-wide emergency

Early in the pandemic, pre-print servers sped rapid evidence sharing. A collaborative of major medical journals supported their use to ensure equitable access to scientific advancements. In the intervening three years, we have made major advancements in the prevention and treatment of COVID-19 and learned about the benefits and limitations of pre-prints as a mechanism for sharing and disseminating scientific knowledge

National Cohort Study of Preoperative Bacteriuria, Surgical Prophylaxis, and Postoperative Outcomes

Abstract Background: Despite recommendations against screening urine for bacteriuria prior to non-urological surgery, it is still a common practice. If the urine culture (Ucx) is positive, clinicians often feel compelled to give targeted therapy or expand the peri-operative prophylaxis (PPX) regimen to cover the urinary organism. Large multicenter studies are lacking. We aimed to evaluate rates and results of preoperative urine screening and postoperative outcomes among a national cohort of surgical patients. Methods: All patients who underwent cardiac, orthopedic implant, or vascular surgery within the national VA health care system during the period from 10/1/08–9/30/13 and had the PPX regimen manually validated were included. Rates of positive Ucx and wound cultures during the 90-day post-operative period were compared between patients with and without pre-operative bacteriuria. Among patients with a positive pre-op urine culture the association between activity of surgical PPX and positive post-op cultures was evaluated. Results: N = 78,810 surgeries were evaluated (21,889 cardiac, 46,565 orthopedic implant, 10,356 vascular). A pre-op Ucx was performed in 26% (Fig); of these, 6.6% were positive and 852 (63%) received PPX active against the uropathogen. Positive pre-op Ucx was associated with higher rates of positive post-op Ucx and wound cultures (Fig). Among patients who received active PPX, post-op Ucx was positive in 46% compared with 39% who received inactive PPX. The rate of post-op wound cultures was not different between patients who received active (25%) vs. inactive (24%) PPX. The pre-op and post-op organisms were the same in 117/221 (52.9%) Ucx and 17/104 (16.3%) wound cultures, respectively. PPX activity did not affect the match rate. Conclusion: This is the largest, multicenter study demonstrating no difference in post-op urine and wound cultures in patients receiving active vs. inactive surgical PPX for pre-op bacteriuria. Prevalence of bacteriuria was similar to other surgical populations. Limitations include predominantly male population and need for further characterization of pre-op antibiotic therapy and UTI and SSI outcomes. Disclosures All authors: No reported disclosures

Health and Economic Burden of Post-Partum Staphylococcus aureus Breast Abscess

Objectives: To determine the health and economic burdens of post-partum Staphylococcus aureus breast abscess. Study design We conducted a matched cohort study (N = 216) in a population of pregnant women (N = 32,770) who delivered at our center during the study period from 10/1/03–9/30/10. Data were extracted from hospital databases, or via chart review if unavailable electronically. We compared cases of S. aureus breast abscess to controls matched by delivery date to compare health services utilization and mean attributable medical costs in 2012 United States dollars using Medicare and hospital-based estimates. We also evaluated whether resource utilization and health care costs differed between cases with methicillin-resistant and -susceptible S. aureus isolates. Results: Fifty-four cases of culture-confirmed post-partum S. aureus breast abscess were identified. Breastfeeding cessation (41%), milk fistula (11.1%) and hospital readmission (50%) occurred frequently among case patients. Breast abscess case patients had high rates of health services utilization compared to controls, including high rates of imaging and drainage procedures. The mean attributable cost of post-partum S. aureus breast abscess ranged from $2,340–$4,012, depending on the methods and data sources used. Mean attributable costs were not significantly higher among methicillin-resistant vs. –susceptible S. aureus cases. Conclusions: Post-partum S. aureus breast abscess is associated with worse health and economic outcomes for women and their infants, including high rates of breastfeeding cessation. Future study is needed to determine the optimal treatment and prevention of these infections

Electronic Detection of MRSA Infections in a National VA Population Augments Current Manual Process

Abstract Background: Automated measurement of hospital-acquired infections (HAIs) can improve the efficiency and reliability of surveillance. Within the VA, inpatient MRSA HAIs are manually reviewed and reported to the Inpatient Evaluation Center (IPEC). These MRSA HAI metrics are used as part of facility rankings to compare quality. However, IPEC uses CDC surveillance definitions which may vary in interpretation across facilities and not reflect all clinically relevant MRSA events. Thus, we sought to compare this manual process to a previously-developed electronic algorithm for detecting clinical MRSA infections to evaluate whether the algorithm could be used to expand MRSA surveillance activities. Methods: Electronic data were extracted from the national VA healthcare system during the period from January 1, 2014–December 31, 2014. The electronic detection algorithm defined MRSA infections as a culture positive for MRSA from a sterile site or from a non-sterile site with receipt of an antimicrobial with MRSA activity ± 5 days from the date of culture collection. Cultures obtained ≥48 hours after admission were classified as HAI. IPEC data for five facilities was extracted and IPEC rates were compared with rates estimated by the electronic algorithm. Flagged infections at one facility were manually reviewed to evaluate any discordances. Results: N = 14,260 MRSA clinical cultures were identified in 9,209 unique patients. Of these, 1,703 met definition for MRSA HAI infection. Electronic algorithm detected MRSA HAI rates varied widely across 137 facilities (Figure 1), ranked by rate per 1,000 patient-days. IPEC rates were universally lower than estimates derived using the MRSA electronic detection tool. Discordance in the estimates was attributable to infections present on admission, differences in capture of surgical site infections, and differences between clinical and surveillance definitions of infection. Conclusion: Applying the MRSA algorithm provided additional information about the burden of MRSA infections across the VA. This algorithm could be used as a tool to complement IPEC reporting and further inform infection prevention activities. Disclosures All authors: No reported disclosures

Immunomodulators for immunocompromised patients hospitalized for COVID-19: a meta-analysis of randomized controlled trials

BACKGROUND: Although immunomodulators have established benefit against the new coronavirus disease (COVID-19) in general, it is uncertain whether such agents improve outcomes without increasing the risk of secondary infections in the specific subgroup of previously immunocompromised patients. We assessed the effect of immunomodulators on outcomes of immunocompromised patients hospitalized for COVID-19.METHODS: The protocol was prospectively registered with PROSPERO (CRD42022335397). MEDLINE, Cochrane Central Register of Controlled Trials and references of relevant articles were searched up to 01-06-2022. Authors of potentially eligible randomized controlled trials were contacted to provide data on immunocompromised patients randomized to immunomodulators vs control (i.e., placebo or standard-of-care).FINDINGS: Eleven randomized controlled trials involving 397 immunocompromised patients hospitalized for COVID-19 were included. Ten trials had low risk of bias. There was no difference between immunocompromised patients randomized to immunomodulators vs control regarding mortality [30/182 (16.5%) vs 41/215 (19.1%); RR 0.93, 95% CI 0.61-1.41; p = 0.74], secondary infections (RR 1.00, 95% CI 0.64-1.58; p = 0.99) and change in World Health Organization ordinal scale from baseline to day 15 (weighed mean difference 0.27, 95% CI -0.09-0.63; p = 0.15). In subgroup analyses including only patients with hematologic malignancy, only trials with low risk of bias, only trials administering IL-6 inhibitors, or only trials administering immunosuppressants, there was no difference between comparators regarding mortality.INTERPRETATION: Immunomodulators, compared to control, were not associated with harmful or beneficial outcomes, including mortality, secondary infections, and change in ordinal scale, when administered to immunocompromised patients hospitalized for COVID-19.FUNDING: Hellenic Foundation for Research and Innovation.</p

Data_Sheet_1_Embracing dynamic public health policy impacts in infectious diseases responses: leveraging implementation science to improve practice.xlsx

RationaleThe host-pathogen relationship is inherently dynamic and constantly evolving. Applying an implementation science lens to policy evaluation suggests that policy impacts are variable depending upon key implementation outcomes (feasibility, acceptability, appropriateness costs) and conditions and contexts.COVID-19 case studyExperiences with non-pharmaceutical interventions (NPIs) including masking, testing, and social distancing/business and school closures during the COVID-19 pandemic response highlight the importance of considering public health policy impacts through an implementation science lens of constantly evolving contexts, conditions, evidence, and public perceptions. As implementation outcomes (feasibility, acceptability) changed, the effectiveness of these interventions changed thereby altering public health policy impact. Sustainment of behavioral change may be a key factor determining the duration of effectiveness and ultimate impact of pandemic policy recommendations, particularly for interventions that require ongoing compliance at the level of the individual.Practical framework for assessing and evaluating pandemic policyUpdating public health policy recommendations as more data and alternative interventions become available is the evidence-based policy approach and grounded in principles of implementation science and dynamic sustainability. Achieving the ideal of real-time policy updates requires improvements in public health data collection and analysis infrastructure and a shift in public health messaging to incorporate uncertainty and the necessity of ongoing changes. In this review, the Dynamic Infectious Diseases Public Health Response Framework is presented as a model with a practical tool for iteratively incorporating implementation outcomes into public health policy design with the aim of sustaining benefits and identifying when policies are no longer functioning as intended and need to be adapted or de-implemented.Conclusions and implicationsReal-time decision making requires sensitivity to conditions on the ground and adaptation of interventions at all levels. When asking about the public health effectiveness and impact of non-pharmaceutical interventions, the focus should be on when, how, and for how long they can achieve public health impact. In the future, rather than focusing on models of public health intervention effectiveness that assume static impacts, policy impacts should be considered as dynamic with ongoing re-evaluation as conditions change to meet the ongoing needs of the ultimate end-user of the intervention: the public.</p