What is modeling?
Modeling is a powerful tool to assist health policy development and disease prevention and control. In NM, COVID-19 modeling helps in planning the State’s response to COVID-19 by attempting to predict the impact of COVID-19 on health systems and populations. However, models are just one tool and should not be considered in isolation from data and lived experiences in the field.
NM COVID-19 Model is the best for our State
Many COVID-19 models have been developed, including state-based, regional, national, and international models. However, the NM model is the best fit for our state for several reasons.
- The NM model is updated daily based on actual NM data, ensuring projections reflect the most recent information.
- The NM model incorporates social distancing and provides risk adjustment for age, disease burden, and social determinants of health by county.
- The NM model considers the unique characteristics of our state, including geographic, socioeconomic, and demographic information.
About New Mexico’s COVID-19 Model
The NM COVID-19 State model is an Enhanced SIR Model, meaning it estimates the number of Susceptible, Infectious, and Recovered (SIR) COVID-19 individuals over time. The State model is developed in partnership with Presbyterian Health Services, Los Alamos National Laboratory, Sandia National Labs, and NMDOH. It incorporates a variety of data sources, including near real-time daily data feeds of:
- COVID-19 case information
- State-wide testing rates
- Geographic distribution of cases and testing
- Clinical outcomes including hospitalization, intensive care, and mechanical ventilation
- Resource capacity and demand
The NM model also considers differences in disease risk using comprehensive data on social determinants of health, the Johns Hopkins Adjusted Clinical Groups, health plan claims data, and delivery system clinical data.
To develop the State model, the NM team consults a variety of evidence-based research and sources. Some of these resources are provided below, and this list will be updated over time.
- Wallinga, J., & Teunis, P. (2004). Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures. American Journal of epidemiology, 160(6), 509-516.
- Briefing Note: Calculation of Effective Reproduction Number, R
- H Juliette Unwin, Swapnil Mishra, Valerie C Bradley et al. State-level tracking of COVID-19 in the United States
(21-05-2020), doi: https://doi.org/10.25561/79231.
New Mexico Modeling Assumptions
To build out the model, NM modelers incorporated the following assumptions:
COVID-19 Epidemiology Modeling Assumptions
*changes weekly based on new data and analysis
|R_Effective* (Mean number of secondary COVID-19 cases produced by one COVID-19 case)||0.9|
|Positive Test Multiplier* (number used to multiply current cases to estimate actual number of cases, as many people with COVID-19 have mild/no symptoms)||3.4|
|Case fatality rate* (proportion of persons with a particular condition who die from that condition. Denominator is number of persons with the condition; numerator is number of cause-specific deaths among those persons)||3.4%|
|Length of hospitalization*||
Medical 5 days
Intensive Care Unit (ICU) 14 days
ICU on Ventilator: 14 days
Medical (excluding ICU): 0.1%
Ventilation Rate: 54.0% of ICU
|Date of initial community spread||3/13/20|
|Reduced Public Gatherings||3/15/20|
|Shelter at home||3/24/20|
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