Effect of wildfire on the prevalence of opioid misuse through anxiety among young adults in the United States: A modeling study.

Background: Exposure to climate change events like wildfires can lead to health and mental health problems. While conceptual frameworks have been hypothesized describing the potential relationship between disaster exposure and substance use, the association remains under-researched and unquantified. Methods: We constructed a quantitative portrayal of one proposed conceptual framework that focuses on the intermediary role of anxiety. We used the Monte Carlo simulation to estimate the impact of wildfire exposure on opioid misuse outcomes through increased anxiety. We searched for and extracted prior empirical evidence on the associations between wildfire anxiety and anxiety-opioid misuse. A base case scenario (S1) was devised in which the impact of wildfire on opioid misuse was limited to increasing anxiety incidence. Two exploratory scenarios investigated the additive roles of altered anxiety phenotype (S2) and increased severity of pre-existing anxiety (S3) due to wildfire exposure. Results: Models show that the prevalence of opioid misuse post-wildfire may rise to 6.0%-7.2%. In S1 (base case), the opioid misuse prevalence ratio was 1.12 (95% uncertainty interval [UI]: 1.00 - 1.27). The two exploratory scenarios, with less stringent assumptions, yielded prevalence ratios of 1.23 (95% UI: 1.00 - 1.51) and 1.34 (95% UI: 1.11 - 1.63). Conclusions: Our modeling study suggests that exposure to wildfires may elevate opioid misuse through increasing anxiety incidence and severity. This may lead to substantial health burdens that may persist long after the initial wildfire event, which may offset recent gains in opioid misuse prevention.

Complementing the United States Household Food Security Survey Module with Items Reflecting Social Unacceptability.

BACKGROUND: Social unacceptability of food access is part of the lived experience of food insecurity but is not assessed as part of the United States Household Food Security Survey Module (HFSSM). OBJECTIVES: The objectives were as follows: 1) to determine the psychometric properties of 2 additional items on social unacceptability in relation to the HFSSM items and 2) to test whether these 2 items provided added predictive accuracy to that of the HFSSM items for mental health outcomes. METHODS: Cross-sectional data used were from the Intersection of Material-Need Insecurities and HIV and Cardiovascular Health substudy of the Multicenter AIDS Cohort Study/Women's Interagency HIV Study Combined Cohort Study. Data on the 10-item HFSSM and 2 new items reflecting social unacceptability were collected between Fall 2020 and Fall 2021 from 1342 participants from 10 United States cities. The 2 social unacceptability items were examined psychometrically in relation to the HFSSM-10 items using models from item response theory. Linear and logistic regression was used to examine prediction of mental health measured by the 20-item Center for Epidemiologic Studies Depression scale and the 10-item Perceived Stress Scale. RESULTS: The social unacceptability items were affirmed throughout the range of severity of food insecurity but with increasing frequency at higher severity of food insecurity. From item response theory models, the subconstructs reflected in the HFSSM-10 and the subconstruct of social unacceptability were distinct, not falling into one dimension. Regression models confirmed that social unacceptability was distinct from the subconstructs reflected in the HFSSM-10. The social unacceptability items as a separate scale explained more (∼1%) variation in mental health than when combined with the HFSSM-10 items in a single scale, and the social unacceptability subconstruct explained more (∼1%) variation in mental health not explained by the HFSSM-10. CONCLUSIONS: Two social unacceptability items used as a separate scale along with the HFSSM-10 predicted mental health more accurately than did the HFSSM-10 alone.

COVID-19 testing protocols to guide duration of isolation: a cost-effectiveness analysis.

BACKGROUND: The Omicron variant of SARS-CoV-2 led to a steep rise in transmissions, and emerging variants continue to influence case rates across the US. As public tolerance for isolation abated, CDC guidance on duration of at-home isolation of COVID-19 cases was shortened to five days if no symptoms, with no laboratory test requirement, despite more cautious approaches advocated by other federal experts. METHODS: We conducted a decision tree analysis of alternative protocols for ending COVID-19 isolation, estimating net costs (direct and productivity), secondary infections, and incremental cost-effectiveness ratios. Sensitivity analyses assessed the impact of input uncertainty. RESULTS: Per 100 individuals, five-day isolation had 23 predicted secondary infections and a net cost of $33,000. Symptom check on day five (CDC guidance) yielded a 23% decrease in secondary infections (to 17.8), with a net cost of $45,000. Antigen testing on day six yielded 2.9 secondary infections and $63,000 in net costs. This protocol, compared to the next best protocol of antigen testing on day five of a maximum eight-day isolation, cost an additional $1,300 per secondary infection averted. Antigen or polymerase chain reaction testing on day five were dominated (more expensive and less effective) versus antigen testing on day six. Results were qualitatively robust to uncertainty in key inputs. CONCLUSIONS: A six-day isolation with antigen testing to confirm the absence of contagious virus appears the most effective and cost-effective de-isolation protocol to shorten at-home isolation of individuals with COVID-19.

COVID-19 Testing Strategies for K-12 Schools in California: A Cost-Effectiveness Analysis.

Public health officials must provide guidance on operating schools safely during the COVID-19 pandemic. Using data from April-December 2021, we conducted a cost-effectiveness analysis to assess six screening strategies for schools using SARS-CoV-2 antigen and PCR tests and varying screening frequencies for 1000 individuals. We estimated secondary infections averted, quality-adjusted life years (QALYs), cost per QALY gained, and unnecessary school days missed per infection averted. We conducted sensitivity analyses for the more transmissible Omicron variant. Weekly antigen testing with PCR follow-up for positives was the most cost-effective option given moderate transmission, adding 0.035 QALYs at a cost of USD 320,000 per QALY gained in the base case (Reff = 1.1, prevalence = 0.2%). This strategy had the fewest needlessly missed school days (ten) per secondary infection averted. During widespread community transmission with Omicron (Reff = 1.5, prevalence = 5.8%), twice weekly antigen testing with PCR follow-up led to 2.02 QALYs gained compared to no test and cost the least (USD 187,300), with 0.5 needlessly missed schooldays per infection averted. In periods of moderate community transmission, weekly antigen testing with PCR follow up can help reduce transmission in schools with minimal unnecessary days of school missed. During widespread community transmission, twice weekly antigen screening with PCR confirmation is the most cost-effective and efficient strategy. Schools may benefit from resources to implement routine asymptomatic testing during surges; benefits decline as community transmission declines.

Indirect COVID-19 health effects and potential mitigating interventions: Cost-effectiveness framework.

BACKGROUND: The COVID-19 pandemic led to important indirect health and social harms in addition to deaths and morbidity due to SARS-CoV-2 infection. These indirect impacts, such as increased depression and substance abuse, can have persistent effects over the life course. Estimated health and cost outcomes of such conditions and mitigation strategies may guide public health responses. METHODS: We developed a cost-effectiveness framework to evaluate societal costs and quality-adjusted life years (QALYs) lost due to six health-related indirect effects of COVID-19 in California. Short- and long-term outcomes were evaluated for the adult population. We identified one evidence-based mitigation strategy for each condition and estimated QALYs gained, intervention costs, and savings from averted health-related harms. Model data were derived from literature review, public data, and expert opinion. RESULTS: Pandemic-associated increases in prevalence across these six conditions were estimated to lead to over 192,000 QALYs lost and to approach $7 billion in societal costs per million population over the life course of adults. The greatest costs and QALYs lost per million adults were due to adult depression. All mitigation strategies assessed saved both QALYs and costs, with five strategies achieving savings within one year. The greatest net savings over 10 years would be achieved by addressing depression ($242 million) and excessive alcohol use ($107 million). DISCUSSION: The COVID-19 pandemic is leading to significant human suffering and societal costs due to its indirect effects. Policymakers have an opportunity to reduce societal costs and health harms by implementing mitigation strategies.

Modeling of overdose and naloxone distribution in the setting of fentanyl compared to heroin.

BACKGROUND: Fentanyl has replaced most other non-prescribed opioids in much of North America. There is controversy over whether a hypothetical reduced efficacy of naloxone in reversing fentanyl is a major contributor to the coincident rising overdose mortality. METHODS: We modified an existing Markov decision analytic model of heroin overdose and naloxone distribution to account for known risks of fentanyl by adjusting overdose risk, the likelihood of death in the event of overdose, and the proportion of cases in which available naloxone was administered in time to prevent death. We assumed near-universal survival when naloxone was administered promptly for heroin or fentanyl overdose, but allowed that to decline in sensitivity analyses for fentanyl. We varied the proportion of use that was fentanyl and adjusted the modified parameters accordingly to estimate mortality as the dominant opioid shifted. RESULTS: Absent naloxone, the annual overdose death rate was 1.0% and 4.1% for heroin and fentanyl, respectively. With naloxone reaching 80% of those at risk, the overdose death rate was 0.7% and 3.6% for heroin and fentanyl, respectively, representing reductions of 26.4% and 12.0%. Monte Carlo simulations resulted in overdose mortality with fentanyl of 3.3-5.2% without naloxone and 2.6-4.9% with naloxone, with 95% certainty. Positing reduced efficacy for naloxone in reversing fentanyl resulted in 3.6% of fentanyl overdose deaths being prevented by naloxone. CONCLUSIONS: Heightened risk for overdose and subsequent death, alongside the time-sensitive need for naloxone administration, fully account for increased mortality when fentanyl replaces heroin, assuming optimal pharmacologic efficacy of naloxone.

Cost-effectiveness of antigen testing for ending COVID-19 isolation.

Background: The Omicron variant of SARS-CoV-2 led to a steep rise in transmissions. Recently, as public tolerance for isolation abated, CDC guidance on duration of at-home isolation of COVID-19 cases was shortened to five days if no symptoms, with no lab test requirement, despite more cautious approaches advocated by other federal experts. Methods: We conducted a decision tree analysis of alternative protocols for ending COVID-19 isolation, estimating net costs (direct and productivity), secondary infections, and incremental cost-effectiveness ratios. Sensitivity analyses assessed the impact of input uncertainty. Results: Per 100 individuals, five-day isolation had 23 predicted secondary infections and a net cost of $33,000. Symptom check on day five (CDC guidance) yielded a 23% decrease in secondary infections (to 17.8), with a net cost of $45,000. Antigen testing on day six yielded 2.9 secondary infections and $63,000 in net costs. This protocol, compared to the next best protocol of antigen testing on day five of a maximum eight-day isolation, cost an additional $1,300 per secondary infection averted. Antigen or polymerase chain reaction testing on day five were dominated (more expensive and less effective) versus antigen testing on day six. Results were qualitatively robust to uncertainty in key inputs. Conclusions: A six-day isolation with antigen testing to confirm the absence of contagious virus appears the most effective and cost-effective de-isolation protocol to shorten at-home isolation of individuals with COVID-19.

Optimal strategies to screen health care workers for COVID-19 in the US: a cost-effectiveness analysis.

BACKGROUND: Transmission of SARS-CoV-2 in health care facilities poses a challenge against pandemic control. Health care workers (HCWs) have frequent and high-risk interactions with COVID-19 patients. We undertook a cost-effectiveness analysis to determine optimal testing strategies for screening HCWs to inform strategic decision-making in health care settings. METHODS: We modeled the number of new infections, quality-adjusted life years lost, and net costs related to six testing strategies including no test. We applied our model to four strata of HCWs, defined by the presence and timing of symptoms. We conducted sensitivity analyses to account for uncertainty in inputs. RESULTS: When screening recently symptomatic HCWs, conducting only a PCR test is preferable; it saves costs and improves health outcomes in the first week post-symptom onset, and costs $83,000 per quality-adjusted life year gained in the second week post-symptom onset. When screening HCWs in the late clinical disease stage, none of the testing approaches is cost-effective and thus no testing is preferable, yielding $11 and 0.003 new infections per 10 HCWs. For screening asymptomatic HCWs, antigen testing is preferable to PCR testing due to its lower cost. CONCLUSIONS: Both PCR and antigen testing are beneficial strategies to identify infected HCWs and reduce transmission of SARS-CoV-2 in health care settings. IgG tests' value depends on test timing and immunity characteristics, however it is not cost-effective in a low prevalence setting. As the context of the pandemic evolves, our study provides insight to health-care decision makers to keep the health care workforce safe and transmissions low.

Optimal strategies to screen health care workers for COVID-19 in the US: a cost-effectiveness analysis.

BACKGROUND: Transmission of SARS-CoV-2 in health care facilities poses a challenge against pandemic control. Health care workers (HCWs) have frequent and high-risk interactions with COVID-19 patients. We undertook a cost-effectiveness analysis to determine optimal testing strategies for screening HCWs to inform strategic decision-making in health care settings. METHODS: We modeled the number of new infections, quality-adjusted life years lost, and net costs related to six testing strategies including no tests. We applied our model to four strata of HCWs, defined by the presence and timing of symptoms. We conducted sensitivity analyses to account for uncertainty in inputs. RESULTS: When screening recently symptomatic HCWs, conducting only a PCR test is preferable; it saves costs and improves health outcomes in the first week post-symptom onset, and costs $83,000 per quality-adjusted life year gained in the second week post-symptom onset. When screening HCWs in the late clinical disease stage, none of the testing approaches is cost-effective and thus no testing is preferable, yielding $11 and 0.003 new infections per 10 HCWs. For screening asymptomatic HCWs, antigen testing is preferable to PCR testing due to its lower cost. CONCLUSIONS: Both PCR and antigen testing are beneficial strategies to identify infected HCWs and reduce transmission of SARS-CoV-2 in health care settings. IgG testing clinical value depends on test timing and immunity characteristics, however is not cost-effective in a low prevalence setting. As the context of the pandemic evolves, our study provides insight to health-care decision makers to keep the health care workforce safe and transmissions low.