Estimation of the prevalence of opioid misuse in New York State counties, 2007-2018: a bayesian spatiotemporal abundance model approach.

An important challenge to addressing the opioid overdose crisis is the lack of information on the size of the population of people who misuse opioids (PWMO) in local areas. This estimate is needed for better resource allocation, estimation of treatment and overdose outcome rates using appropriate denominators (ie, the population at risk), and proper evaluation of intervention effects. In this study, we used a bayesian hierarchical spatiotemporal integrated abundance model that integrates multiple types of county-level surveillance outcome data, state-level information on opioid misuse, and covariates to estimate the latent (hidden) numbers of PWMO and latent prevalence of opioid misuse across New York State counties (2007-2018). The model assumes that each opioid-related outcome reflects a partial count of the number of PWMO, and it leverages these multiple sources of data to circumvent limitations of parameter estimation associated with other types of abundance models. Model estimates showed a reduction in the prevalence of PWMO during the study period, with important spatial and temporal variability. The model also provided county-level estimates of rates of treatment and opioid overdose using the numbers of PWMO as denominators. This modeling approach can identify the sizes of hidden populations to guide public health efforts in confronting the opioid overdose crisis across local areas. This article is part of a Special Collection on Mental Health.

The role of prescription opioid and cannabis supply policies on opioid overdose deaths.

Mandatory prescription drug monitoring programs and cannabis legalization have been hypothesized to reduce overdose deaths. We examined associations between prescription monitoring programs with access mandates ("must-query PDMPs"), legalization of medical and recreational cannabis supply, and opioid overdose deaths in United States counties in 2013-2020. Using data on overdose deaths from the National Vital Statistics System, we fit Bayesian spatiotemporal models to estimate risk differences and 95% credible intervals (CrI) in county-level opioid overdose deaths associated with enactment of these state policies. Must-query PDMPs were independently associated with on average 0.8 (95% CrI: 0.5, 1.0) additional opioid-involved overdose deaths per 100,000 person-years. Legal cannabis supply was not independently associated with opioid overdose deaths in this time period. Must-query PDMPs enacted in the presence of legal (medical or recreational) cannabis supply were associated with 0.7 (95% CrI: 0.4, 0.9) more opioid-involved deaths, relative to must-query PDMPs without any legal cannabis supply. In a time when overdoses are driven mostly by non-prescribed opioids, stricter opioid prescribing policies and more expansive cannabis legalization were not associated with reduced overdose death rates.

State-Level Firearm Laws and Firearm Homicide in US Cities: Heterogenous Associations by City Characteristics.

Despite well-studied associations of state firearm laws with lower state- and county-level firearm homicide, there is a shortage of studies investigating differences in the effects of distinct state firearm law categories on various cities within the same state using identical methods. We examined associations of 5 categories of state firearm laws-pertaining to buyers, dealers, domestic violence, gun type/trafficking, and possession-with city-level firearm homicide, and then tested differential associations by city characteristics. City-level panel data on firearm homicide cases of 78 major cities from 2010 to 2020 was assessed from the Centers for Disease Control and Prevention's National Vital Statistics System. We modeled log-transformed firearm homicide rates as a function of firearm law scores, city, state, and year fixed effects, along with time-varying city-level confounders. We considered effect measure modification by poverty, unemployment, vacant housing, and income inequality. A one z-score increase in state gun type/trafficking, possession, and dealer law scores was associated with 25% (95% confidence interval [CI]:-0.37,-0.1), 19% (95% CI:-0.29,-0.07), and 17% (95% CI:-0.28, -0.4) lower firearm homicide rates, respectively. Protective associations were less pronounced in cities with high unemployment and high housing vacancy, but more pronounced in cities with high income inequality. In large US cities, state-level gun type/trafficking, possession, and dealer laws were associated with lower firearm homicide rates, but buyers and domestic violence laws were not. State firearm laws may have differential effects on firearm homicides based on city characteristics, and city-wide policies to enhance socioeconomic drivers may add benefits of firearm laws.

Changes in Opioid and Benzodiazepine Poisoning Deaths After Cannabis Legalization in the US: A County-level Analysis, 2002-2020.

BACKGROUND: Cannabis legalization for medical and recreational purposes has been suggested as an effective strategy to reduce opioid and benzodiazepine use and deaths. We examined the county-level association between medical and recreational cannabis laws and poisoning deaths involving opioids and benzodiazepines in the US from 2002 to 2020. METHODS: Our ecologic county-level, spatiotemporal study comprised 49 states. Exposures were state-level implementation of medical and recreational cannabis laws and state-level initiation of cannabis dispensary sales. Our main outcomes were poisoning deaths involving any opioid, any benzodiazepine, and opioids with benzodiazepines. Secondary analyses included overdoses involving natural and semi-synthetic opioids, synthetic opioids, and heroin. RESULTS: Implementation of medical cannabis laws was associated with increased deaths involving opioids (rate ratio [RR] = 1.14; 95% credible interval [CrI] = 1.11, 1.18), benzodiazepines (RR = 1.19; 95% CrI = 1.12, 1.26), and opioids+benzodiazepines (RR = 1.22; 95% CrI = 1.15, 1.30). Medical cannabis legalizations allowing dispensaries was associated with fewer deaths involving opioids (RR = 0.88; 95% CrI = 0.85, 0.91) but not benzodiazepine deaths; results for recreational cannabis implementation and opioid deaths were similar (RR = 0.81; 95% CrI = 0.75, 0.88). Recreational cannabis laws allowing dispensary sales was associated with consistent reductions in opioid- (RR = 0.83; 95% CrI = 0.76, 0.91), benzodiazepine- (RR = 0.79; 95% CrI = 0.68, 0.92), and opioid+benzodiazepine-related poisonings (RR = 0.83; 95% CrI = 0.70, 0.98). CONCLUSIONS: Implementation of medical cannabis laws was associated with higher rates of opioid- and benzodiazepine-related deaths, whereas laws permitting broader cannabis access, including implementation of recreational cannabis laws and medical and recreational dispensaries, were associated with lower rates. The estimated effects of the expanded availability of cannabis seem dependent on the type of law implemented and its provisions.

Mental health Narrative Community-Based Group Therapy in violence-displaced Afro-Colombians: a randomized controlled trial.

This study aims to evaluate the effect of a mental health Narrative Community-Based Group Therapy (NCGT) in Afro-Colombian violence survivors. A randomized controlled trial was conducted in Buenaventura and Quibdó, Colombia. Afro-Colombian adults (n=521) were randomly allocated to a NCGT (n1=175), a wait-control group (n2=171) or a Common Elements Treatment Approach (CETA, n3=175). The CETA was described separately given conceptual/methodological differences. Lay psychosocial community workers delivered the NCGT. Symptoms were assessed before and after intervention/wait with culturally adapted mental health symptoms and gender-specific functionality scales. Intent to treat analysis and mean difference of differences were used for comparisons. In Buenaventura, a significant reduction in functional impairment (mean difference: -0.30, 95% Confidence Interval [95% CI]: -0.55, -0.05) and depression (mean difference: -0.24, 95% CI: -0.42, -0.07) were found, with small and moderate effect size, respectively. In Quibdó, functionality improved significantly (mean difference: -0.29, 95% CI: -0.54, -0.04, small effect size). Even though differences in depression and anxiety were not significant, there were reductions in symptoms. The NCGT is effective in improving daily functioning among violence victims in the Colombian Pacific and has the potential to reduce symptoms of depression. Further exploration is required to understand the effects of a narrative group therapy for mental health in Afro-Colombian populations.Trial Registration: ClinicalTrials.gov number: NCT01856673 (https://clinicaltrials.gov/ct2/show/NCT01856673).

A Systematic Review of Simulation Models to Track and Address the Opioid Crisis.

The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models are a tool to help us understand and address thiscomplex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings; created a database of model parameters used for model calibration; and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and agent-based models (16%). Intervention cost-effectiveness was evaluated in 40% of the studies, and 39% focused on services for people with opioid use disorder (OUD). In 61% of the eligible articles, authors discussed calibrating their models to empirical data, and in 31%, validation approaches used in the modeling process were discussed. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation or relapse, emergency medical services, and death parameters. From this database, potential model inputs can be identified and models can be compared with prior work. Simulation models should be used to tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.

Suicidal ideation and attempts following nonmedical use of prescription opioids and related disorder.

BACKGROUND: Since 1999, the rate of fatal prescription opioid overdoses and of suicides has dramatically increased in the USA. These increases, which have occurred among similar demographic groups, have led to the hypothesis that the opioid epidemic contributed to increases in suicidal behavior, though the underlying association remains poorly defined. We examine the association between nonmedical use of prescription opioids/opioid use disorder and suicidal ideation/attempts. METHODS: We used longitudinal data from a national representative sample of the US adult population, the National Epidemiologic Survey on Alcohol and Related Conditions. Participants (n = 34 653) were interviewed in 2001-2002 (wave 1) and re-interviewed approximately 3 years later (wave 2). A propensity score analysis estimated the association between exposure to prescription opioids at wave 1 and prevalent/incident suicidal behavior at wave 2. RESULTS: Heavy/frequent (⩾2-3 times a month) prescription opioid use was associated with prevalent suicide attempts [adjusted risk ratio (ARR) = 2.75, 95% CI 1.35-5.60]. Prescription opioid use disorder was associated with prevalent (ARR = 1.98, 95% CI 1.20-3.28) and incident suicidal ideation (ARR = 2.59, 95% CI 1.25-5.37), and prevalent attempts (ARR = 4.19, 95% CI 1.71-10.27). None of the exposures was associated with incident suicide attempts. CONCLUSIONS: Heavy/frequent opioid use and related disorder were associated with prevalent suicide attempts; opioid use disorder was also associated with the incident and prevalent suicidal ideation. Given population increases in nonmedical use of prescription opioids and disorder, the opioid crisis may have contributed to population increases in suicidal ideation.

Homicide Epidemic in Cali, Colombia: A Surveillance System Data Analysis, 1993‒2018.

Objectives. To examine homicide rates in Cali, Colombia, during the 1993-2018 period, using information derived from an interagency surveillance system. Methods. We used homicide data from Cali's Epidemiological Surveillance System to examine homicide trends by victim's age and sex, time, and type of method used. We estimated trend changes and the annual percentage changes using joinpoint regression analyses. Results. Homicide rates per 100 000 inhabitants dropped from 102 in 1993 to 47.8 in 2018. We observed reductions in homicide rates across age and sex groups. Most homicide victims were men aged 20 to 39 years from poor, marginalized areas. Firearms were used in 84.9% of all cases. The average annual percentage change for the entire period was -3.6 (95% confidence interval = -6.7, -0.4). Conclusions. Fluctuations in homicide rates in Cali show a clear epidemic pattern, occurring concurrently with the "crack epidemic" in different countries. Reliable and timely information provided by an Epidemiological Surveillance System allowed opportune formulation of public policies to reduce the impact of violence in Cali.

Do parenting behaviors modify the way sensation seeking influences antisocial behaviors?

BACKGROUND: Parenting behaviors have been shown to moderate the association between sensation seeking and antisocial behaviors. METHODS: Data were obtained from the Boricua Youth Study, a longitudinal study of 2,491 Puerto Rican youth living in the South Bronx, New York, and the metropolitan area of San Juan, Puerto Rico. First, we examined the prospective relationship between sensation seeking and antisocial behaviors across 3 yearly waves and whether this relationship varied by sociodemographic factors. Second, we examined the moderating role of parenting behaviors-including parental monitoring, warmth, and coercive discipline-on the prospective relationship between sensation seeking and antisocial behaviors. RESULTS: Sensation seeking was a strong predictor of antisocial behaviors for youth across two different sociocultural contexts. High parental monitoring buffered the association between sensation seeking and antisocial behaviors, protecting individuals with this trait. Low parental warmth was associated with high levels of antisocial behaviors, regardless of the sensation seeking level. Among those with high parental warmth, sensation seeking predicted antisocial behaviors, but the levels of antisocial behaviors were never as high as those of youth with low parental warmth. CONCLUSIONS: Study findings underscore the relevance of person-family context interactions in the development of antisocial behaviors. Future interventions should focus on the interplay between individual vulnerabilities and family context to prevent the unhealthy expression of a trait that is present in many individuals.

Suicide Mortality in Canada after the Death of Robin Williams, in the Context of High-Fidelity to Suicide Reporting Guidelines in the Canadian Media.

BACKGROUND: Evidence suggests that suicide mortality increases after high-profile suicide deaths. Indeed, suicide in the United States increased disproportionately after the suicide by suffocation of well-known comedian Robin Williams in August 2014. Such increases are often attributed to irresponsible media coverage of the suicide contributing to "copycat suicides." However, recent research indicates that the mainstream Canadian media have significantly improved their suicide coverage, with high fidelity to suicide reporting guidelines after Williams' death. As such, the aim of the present study is to examine suicide mortality in Canada after Robin Williams' suicide. METHODS: We obtained deidentified monthly suicide count data from January 1999 to December 2015 stratified by age, sex, and method of suicide from Statistics Canada. We used time-series analyses to estimate the expected number of suicides in the months following Robin Williams' death. This was done using a seasonal autoregressive integrated moving averages (SARIMA) method. Expected suicides were then compared with observed suicides. RESULTS: August 2014 was the month with the highest number of suicides from 2010 to 2015. The time-series model indicated a 16% increase in the expected number of suicides during the months from August to December 2014 inclusive. Moreover, males over 30 had the greatest number of excess suicides, and suicides by suffocation (the method used by Robin Williams) were also higher in August and the following months. INTERPRETATION: Suicides increased in Canada after Robin Williams' death, despite the improved mainstream media coverage witnessed in other studies. Other factors (e.g., social and alternative media) may have contributed to the observed increase in suicide.

Impact of Medical Marijuana Laws on State-Level Marijuana Use by Age and Gender, 2004-2013.

In states that have passed medical marijuana laws (MMLs), marijuana use (MU) increased after MML enactment among people ages 26 and older, but not among ages 12-25. We examined whether the age-specific impact of MMLs on MU varied by gender. Data were obtained from the 2004-2013 restricted-use National Survey on Drug Use and Health, aggregated at the state level. The exposure was a time-varying indicator of state-level MML (0 = No Law, 1 = Before Law, 2 = After Law). Outcomes included past-month MU prevalence, daily MU prevalence among past-year users (i.e., 300+ days/year), and past-year marijuana use disorder (MUD) prevalence. Linear models tested the state-level MML effect on outcomes by age (12-17, 18-25, 26+) and gender. Models included a state-level random intercept and controlled for time- and state-level covariates. Past-month MU did not increase after enactment of MML in men or women ages 12-25. Among people 26+, past-month MU increased for men from 7.0% before to 8.7% after enactment (+ 1.7%, p < 0.001) and for women from 3.1% before to 4.3% after enactment (+ 1.1%, p = 0.013). Among users 26+, daily MU also increased after enactment in both genders (men 16.3 to 19.1%, + 2.8%, p = 0.014; women 9.2 to 12.7%, + 3.4%, p = 0.003). There were no statistically significant increases in past-year MUD prevalence for any age or gender group after MML enactment. Given the statistically significant increase in daily use among past-year users aged 26+ following enactment, education campaigns should focus on informing the public of the risks associated with regular marijuana use.

US Traffic Fatalities, 1985-2014, and Their Relationship to Medical Marijuana Laws.

OBJECTIVES: To determine the association of medical marijuana laws (MMLs) with traffic fatality rates. METHODS: Using data from the 1985-2014 Fatality Analysis Reporting System, we examined the association between MMLs and traffic fatalities in multilevel regression models while controlling for contemporaneous secular trends. We examined this association separately for each state enacting MMLs. We also evaluated the association between marijuana dispensaries and traffic fatalities. RESULTS: On average, MML states had lower traffic fatality rates than non-MML states. Medical marijuana laws were associated with immediate reductions in traffic fatalities in those aged 15 to 24 and 25 to 44 years, and with additional yearly gradual reductions in those aged 25 to 44 years. However, state-specific results showed that only 7 states experienced post-MML reductions. Dispensaries were also associated with traffic fatality reductions in those aged 25 to 44 years. CONCLUSIONS: Both MMLs and dispensaries were associated with reductions in traffic fatalities, especially among those aged 25 to 44 years. State-specific analysis showed heterogeneity of the MML-traffic fatalities association, suggesting moderation by other local factors. These findings could influence policy decisions on the enactment or repealing of MMLs and how they are implemented.

What Do We Know About the Association Between Firearm Legislation and Firearm-Related Injuries?

Firearms account for a substantial proportion of external causes of death, injury, and disability across the world. Legislation to regulate firearms has often been passed with the intent of reducing problems related to their use. However, lack of clarity around which interventions are effective remains a major challenge for policy development. Aiming to meet this challenge, we systematically reviewed studies exploring the associations between firearm-related laws and firearm homicides, suicides, and unintentional injuries/deaths. We restricted our search to studies published from 1950 to 2014. Evidence from 130 studies in 10 countries suggests that in certain nations the simultaneous implementation of laws targeting multiple firearms restrictions is associated with reductions in firearm deaths. Laws restricting the purchase of (e.g., background checks) and access to (e.g., safer storage) firearms are also associated with lower rates of intimate partner homicides and firearm unintentional deaths in children, respectively. Limitations of studies include challenges inherent to their ecological design, their execution, and the lack of robustness of findings to model specifications. High quality research on the association between the implementation or repeal of firearm legislation (rather than the evaluation of existing laws) and firearm injuries would lead to a better understanding of what interventions are likely to work given local contexts. This information is key to move this field forward and for the development of effective policies that may counteract the burden that firearm injuries pose on populations.

State Medical Marijuana Laws and the Prevalence of Opioids Detected Among Fatally Injured Drivers.

OBJECTIVES: To assess the association between medical marijuana laws (MMLs) and the odds of a positive opioid test, an indicator for prior use. METHODS: We analyzed 1999-2013 Fatality Analysis Reporting System (FARS) data from 18 states that tested for alcohol and other drugs in at least 80% of drivers who died within 1 hour of crashing (n = 68 394). Within-state and between-state comparisons assessed opioid positivity among drivers crashing in states with an operational MML (i.e., allowances for home cultivation or active dispensaries) versus drivers crashing in states before a future MML was operational. RESULTS: State-specific estimates indicated a reduction in opioid positivity for most states after implementation of an operational MML, although none of these estimates were significant. When we combined states, we observed no significant overall association (odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.61, 1.03). However, age-stratified analyses indicated a significant reduction in opioid positivity for drivers aged 21 to 40 years (OR = 0.50; 95% CI = 0.37, 0.67; interaction P < .001). CONCLUSIONS: Operational MMLs are associated with reductions in opioid positivity among 21- to 40-year-old fatally injured drivers and may reduce opioid use and overdose.

Inequality on the frontline: A multi-country study on gender differences in mental health among healthcare workers during the COVID-19 pandemic.

Healthcare workers (HCWs) were at increased risk for mental health problems during the COVID-19 pandemic, with prior data suggesting women may be particularly vulnerable. Our global mental health study aimed to examine factors associated with gender differences in psychological distress and depressive symptoms among HCWs during COVID-19. Across 22 countries in South America, Europe, Asia and Africa, 32,410 HCWs participated in the COVID-19 HEalth caRe wOrkErS (HEROES) study between March 2020 and February 2021. They completed the General Health Questionnaire-12, the Patient Health Questionnaire-9 and questions about pandemic-relevant exposures. Consistently across countries, women reported elevated mental health problems compared to men. Women also reported increased COVID-19-relevant stressors, including insufficient personal protective equipment and less support from colleagues, while men reported increased contact with COVID-19 patients. At the country level, HCWs in countries with higher gender inequality reported less mental health problems. Higher COVID-19 mortality rates were associated with increased psychological distress merely among women. Our findings suggest that among HCWs, women may have been disproportionately exposed to COVID-19-relevant stressors at the individual and country level. This highlights the importance of considering gender in emergency response efforts to safeguard women's well-being and ensure healthcare system preparedness during future public health crises.

Do Trajectories of Sensation Seeking Vary by Sex and Child Maltreatment Subtypes?

Child maltreatment and elevated sensation seeking are associated with a wide range of negative outcomes. Longitudinal data from a study of Puerto Ricans living in two sociocultural contexts were used to determine whether child maltreatment subtypes, sex, or sociocultural context relate to trajectories of sensation seeking. Participants were 2,489 individuals from the Boricua Youth Study (48.5% girls) living in New York and in Puerto Rico (PR; 5-15 years old at Wave 1). Subtypes of child maltreatment were measured using child report on the Parent-Child Conflict Tactics Scale and the Sexual Victimization Scale at Wave 1. The association between child maltreatment subtypes, sex, sociocultural context, and previously established sensation-seeking trajectories across three waves of data collection was probed using multinomial logistic regression. Girls, but not boys, who experienced neglect (adjusted odds ratio; AOR; 95% confidence interval [95% CI] = 5.33 [1.35, 21.03]), or physical abuse (AOR [95% CI] = 3.66 [1.07, 12.54]), were more likely to have an elevated sensation-seeking trajectory than a normative trajectory. For boys, none of the maltreatment subtypes were linked to the elevated sensation-seeking class. Girls exposed to verbal abuse (AOR [95% CI] = 0.33 [0.15, 0.75]) and boys exposed to physical abuse (AOR [95% CI] = 0.39 [0.16, 0.97]) were less likely to belong to the low sensation-seeking class. No significant interactions between sociocultural context (i.e., PR vs. New York) and maltreatment subtype on the development of sensation seeking were found. This research suggests sensation-seeking levels vary by experiences of childhood maltreatment, and that sex moderates the relationship between child maltreatment experiences and sensation seeking, with an association between some maltreatment subtypes and elevated sensation-seeking trajectories found in girls, but not boys. These results underline the importance of considering sex when examining how child maltreatment relates to outcomes.

SARS-CoV-2 diagnostic testing alternatives for Latin America.

In the past four months SARS-CoV-2 has reached most countries in the world. Public health strategies based on widespread testing and proper isolation of positive cases have shown to be helpful to reduce local transmission of SARS-CoV-2. Confirmatory tests, that identify viral RNA, and screening serological tests that identify viral antigens or host antibodies against viral proteins are part of the tools that nations can use to fight infectious disease epidemics. Understanding how each test works can provide insights about their test characteristics and how they can be used for different clinical and public health goals. Testing is a key strategy to reduce viral transmission, not only for this epidemic, but also for others to come.

En los últimos cuatro meses, el virus SARS-CoV-2 ha llegado a la mayoría de países en el mundo. Las estrategias de salud pública basadas en la realización masiva de pruebas diagnósticas y el aislamiento focalizado de casos positivos han demostrado ser útiles para la reducción de la transmisión de SARS-CoV-2. Las pruebas confirmatorias, que identifican el ARN viral, y las pruebas serológicas que identifican antígenos virales o anticuerpos contra las proteínas virales del huésped son herramientas que las naciones pueden usar para combatir las epidemias producidas por agentes infecciosos. El comprender cómo funcionan estas pruebas puede ayudar a entender sus características y cómo pueden ser usadas para diferentes objetivos clínicos y de salud pública. Las pruebas diagnósticas son herramientas clave para reducir la transmisión viral, no solo en esta epidemia, sino para otras por venir.

Mathematical model and COVID-19.

Currently, there are several mathematical models that have been developed to understand the dynamics of COVID-19 infection. However, the difference in the sociocultural contexts between countries requires the specific adjustment of these estimates to each scenario. This article analyses the main elements used for the construction of models from epidemiological patterns, to describe the interaction, explain the dynamics of infection and recovery, and to predict possible scenarios that may arise with the introduction of public health measures such as social distancing and quarantines, specifically in the case of the pandemic unleashed by the new SARS-CoV-2/COVID-19 virus. COMMENT: Mathematical models are highly relevant for making objective and effective decisions to control and eradicate the disease. These models used for COVID-19 have supported and will continue to provide information for the selection and implementation of programs and public policies that prevent associated complications, reduce the speed of the virus spread and minimize the occurrence of severe cases of the disease that may collapse health systems.

En la actualidad existen varios modelos matemáticos que han sido desarrollados para entender la dinámica de la infección por COVID-19. Sin embargo, la diferencia en los contextos socioculturales entre países hace necesario el ajuste específico de estas estimaciones a cada escenario. Este artículo analiza los principales elementos usados para la construcción de los modelos a partir de patrones epidemiológicos, para lograr describir la interacción, explicar la dinámica de infección y recuperación, así como para predecir posibles escenarios que pueden presentarse con la introducción de medidas en salud pública como el distanciamiento social y cuarentenas, específicamente para el caso de la pandemia desatada por el nuevo virus SARS-CoV-2/COVID-19. COMENTARIO: Los modelos matemáticos son de gran relevancia para la toma de decisiones objetivas y eficaces para controlar y erradicar la enfermedad. Estos modelos usados para el COVID-19, han apoyado y seguirán aportando información para la selección e implementación de programas y políticas públicas que prevengan complicaciones asociadas, disminuyan la velocidad de propagación del virus y minimicen la aparición de casos severos de enfermedad que puedan colapsar los sistemas de salud.