Effective responses to the COVID-19 pandemic require integrating behavioral factors such as risk-driven contact reduction, improved treatment, and adherence fatigue with asymptomatic transmission, disease acuity, and hospital capacity. We build one such model and estimate it for all 92 nations with reliable testing data. Cumulative cases and deaths through 22 December 2020 are estimated to be 7.03 and 1.44 times official reports, yielding an infection fatality rate (IFR) of 0.51 percent, which has been declining over time. Absent adherence fatigue, cumulative cases would have been 47 percent lower. Scenarios through June 2021 show that modest improvement in responsiveness could reduce cases and deaths by about 14 percent, more than the impact of vaccinating half of the population by that date. Variations in responsiveness to risk explain two orders of magnitude difference in per-capita deaths despite reproduction numbers fluctuating around one across nations. A public online simulator facilitates scenario analysis over the coming months.

Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers’ capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.

Significance The opioid crisis remains one of the greatest public health challenges in the United States. The crisis is complex, with long delays and feedbacks between policy actions and their effects, which creates a risk of unintended consequences and complicates policy decision-making. We present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), an operationally detailed national-level model of the opioid crisis, intended to enhance understanding of the crisis and guide policy decisions. Drawing on multiple data sources, SOURCE replicates how risks of opioid misuse initiation and overdose have evolved over time in response to behavioral and other changes and suggests how those risks may evolve in the future, providing a basis for projecting and analyzing potential policy impacts and solutions.

Limited and inconsistent testing and differences in age distribution, health care resources, social distancing, and policies have caused large variations in the extent and dynamics of the COVID-19 pandemic across nations, complicating the estimation of prevalence, the infection fatality rate (IFR), and other factors important to care providers and policymakers. Using data for all 84 countries with reliable testing data (spanning 4.75 billion people) we develop a dynamic epidemiological model integrating data on cases, deaths, excess mortality and other factors to estimate how asymptomatic transmission, disease acuity, hospitalization, and behavioral and policy responses to risk condition prevalence and IFR across nations and over time. For these nations we estimate IFR averages 0.68% (0.64%-0.7%). Cases and deaths through June 18, 2020 are estimated to be 11.8 and 1.48 times official reports, respectively, at 88.5 (85-95.3) million and 600 (586-622) thousand. Prevalence and IFR vary substantially, e.g., Ecuador (18%; 0.61%), Chile (15.5%; 0.57%), Mexico (8.8%; 0.69%), Iran (7.9%; 0.44%), USA (5.3%; 0.99%), UK (5.2%; 1.59%), Iceland (1.65%, 0.56%), New Zealand (0.1%, 0.64%), but all nations remain well below the level needed for herd immunity. By alerting the public earlier and reducing contacts, extensive testing when the pandemic was declared could have averted 35.3 (32.7-42.7) million cases and 197 (171-232) thousand deaths. However, future outcomes are less dependent on testing and more contingent on the willingness of communities and governments to reduce transmission. Absent breakthroughs in treatment or vaccination and with mildly improved responses we project 249 (186-586) million cases and 1.75 (1.40-3.67) million deaths in the 84 countries by Spring 2021.

Introduction: The opioid crisis is a pervasive public health threat in the U.S. Simulation modeling approaches that integrate a systems perspective are used to understand the complexity of this crisis and analyze what policy interventions can best address it. However, limitations in currently available data sources can hamper the quantification of these models. Methods: To understand and discuss data needs and challenges for opioid systems modeling, a meeting of federal partners, modeling teams, and data experts was held at the U.S. Food and Drug Administration in April 2019. This paper synthesizes the meeting discussions and interprets them in the context of ongoing simulation modeling work. Results: The current landscape of national-level quantitative data sources of potential use in opioid systems modeling is identified, and significant issues within data sources are discussed. Major recommendations on how to improve data sources are to: maintain close collaboration among modeling teams, enhance data collection to better fit modeling needs, focus on bridging the most crucial information gaps, engage in direct and regular interaction between modelers and data experts, and gain a clearer definition of policymakers' research questions and policy goals. Conclusions: This article provides an important step in identifying and discussing data challenges in opioid research generally and opioid systems modeling specifically. It also identifies opportunities for systems modelers and government agencies to improve opioid systems models.

Objectives: Because buprenorphine treatment of opioid use disorder reduces opioid overdose deaths (OODs), expanding access to care is an important policy and clinical care goal. Policymakers must choose within capacity limitations whether to expand the number of people with opioid use disorder who are treated or extend duration for existing patients. This inherent tradeoff could be made less acute with expanded buprenorphine treatment capacity. Methods: To inform such decisions, we used a validated simulation model to project the effects of increasing buprenorphine treatmentseeking, average episode duration, and capacity (patients per provider) on OODs in the United States from 2023 to 2033, varying the start time to assess the effects of implementation delays. Results: Results show that increasing treatment duration alone could cost lives in the short term by reducing capacity for new admissions yet save more lives in the long term than accomplished by only increasing treatment seeking. Increasing provider capacity had negligible effects. The most effective 2-policy combination was increasing capacity and duration simultaneously, which would reduce OODs up to 18.6% over a decade. By 2033, the greatest reduction in OODs (≥20%) was achieved when capacity was doubled and average duration reached 2 years, but only if the policy changes started in 2023. Delaying even a year diminishes the benefits. Treatment-seeking increases were equally beneficial whether they began in 2023 or 2025 but of only marginal benefit beyond what capacity and duration achieved.Conclusions: If policymakers only target 2 policies to reduce OODs, they should be to increase capacity and duration, enacted quickly and aggressively.

Responses to the COVID-19 pandemic have been conditioned by a perceived tradeoff between saving lives and the economic costs of contact-reduction measures. We develop a model of SARS-CoV-2 transmission where populations endogenously reduce contacts in response to the risk of death. We estimate the model for 118 countries and assess the existence of a tradeoff between death rates and changes in contacts. In this model communities go through three phases – rapid early outbreaks, control through initial response, and a longer period of quasi-equilibrium endemic infection with effective reproduction number (Re) fluctuating around one. Analytical characterization of this phase shows little tradeoff between contact reduction levels (underpinning economic costs) and death rates. Empirically estimating the model, we find no positive correlation between (log) death rates and (normalized) contact levels across nations, whether contacts are estimated based on epidemic curves or mobility data. While contact reduction levels are broadly similar across countries, expected death rates vary greatly, by two orders of magnitude (5-95 percentile: 0.03-17 deaths per million per day). Results suggest nations could significantly reduce the human toll of the pandemic without more disruption to normal social and economic activity than they have already faced.Executive SummaryProblem specification: The response to COVID-19 pandemic is dominated by a perceived tradeoff between saving lives through cutting social interactions vs. allowing those interactions to maintain economic livelihood of communities. It is, however, unclear if this tradeoff really exists.Practitioner audience: Local, regional, and national policy makers who control communities’ responses to observed levels of COVID-19 transmission risk are grappling with this perceived tradeoff on a daily basis.Core insight: The perceived tradeoff is illusory. Every community will pay a similar price in contact reduction. What communities do control is the level of infection and deaths at which they are willing to bring down contacts enough to keep the epidemic from growing further.Practical implications: By becoming more responsive, effective leaders quickly bring down community’s interactions in response to small numbers of cases and deaths. They can then maintain these small case counts at social interaction levels similar to other communities that experience much larger ongoing cases. Thus, there is a path to saving lives at limited excess costs.

In 2020, the ongoing U.S. opioid overdose crisis collided with the emerging COVID-19 pandemic. Opioid overdose deaths (OODs) rose an unprecedented 38%, due to a combination of COVID-19 disrupting services essential to people who use drugs, continued increases in fentanyls in the illicit drug supply, and other factors. How much did these factors contribute to increased OODs? We used a validated simulation model of the opioid overdose crisis, SOURCE, to estimate excess OODs in 2020 and the distribution of that excess attributable to various factors. Factors affecting OODs that could have been disrupted by COVID-19, and for which data were available, included opioid prescribing, naloxone distribution, and receipt of medications for opioid use disorder. We also accounted for fentanyls’ presence in the heroin supply. We estimated a total of 18,276 potential excess OODs, including 1,792 lives saved due to increases in buprenorphine receipt and naloxone distribution and decreases in opioid prescribing. Critically, growth in fentanyls drove 43% (7,879) of the excess OODs. A further 8% is attributable to first-ever declines in methadone maintenance treatment and extended-released injectable naltrexone treatment, most likely due to COVID-19-related disruptions. In all, 49% of potential excess OODs remain unexplained, at least some of which are likely due to additional COVID-19-related disruptions. While the confluence of various COVID-19-related factors could have been responsible for more than half of excess OODs, fentanyls continued to play a singular role in excess OODs, highlighting the urgency of mitigating their effects on overdoses.