Testing and vaccination to reduce the impact of COVID-19 in nursing homes: an agent-based approach

Abstract

Background Efforts to protect residents in nursing homes involve non-pharmaceutical interventions, testing, and vaccine. We sought to quantify the effect of testing and vaccine strategies on the attack rate, length of the epidemic, and hospitalization. Methods We developed an agent-based model to simulate the dynamics of SARS-CoV-2 transmission among resident and staff agents in a nursing home. Interactions between 172 residents and 170 staff based on data from a nursing home in Los Angeles, CA. Scenarios were simulated assuming different levels of non-pharmaceutical interventions, testing frequencies, and vaccine efficacy to reduce transmission. Results Under the hypothetical scenario of widespread SARS-CoV-2 in the community, 3-day testing frequency minimized the attack rate and the time to eradicate an outbreak. Prioritization of vaccine among staff or staff and residents minimized the cumulative number of infections and hospitalization, particularly in the scenario of high probability of an introduction. Reducing the probability of a viral introduction eased the demand on testing and vaccination rate to decrease infections and hospitalizations. Conclusions Improving frequency of testing from 7-days to 3-days minimized the number of infections and hospitalizations, despite widespread community transmission. Vaccine prioritization of staff provides the best protection strategy when the risk of viral introduction is high.

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

“…Heterogeneous vaccine was indicated for high-income countries in two (0.5%) articles [ 106 , 382 ]. In 95 articles (23.1%), the difference in days between administered doses were considered; out of these, 22 articles (23.2%) considered a 21-day interval between doses [ 55 , 60 , 69 , 100 , 122 , 133 , 134 , 140 , 187 , 216 , 217 , 221 , 302 , 303 , 329 , 330 , 335 , 342 , 383 , 384 , 424 , 425 ], while 22 (23.2%) considered a period of 21- to 28-day interval [ 42 , 90 , 116 , 119 – 121 , 136 , 142 , 151 , 155 , 184 , 204 , 205 , 258 , 260 , 273 , 324 , 328 , 351 , 354 , 356 , 366 ]. Additionally, 11 (11.6%) articles considered a period equal to or greater than three months [ 203 , 211 , 222 , 269 , 300 , 314 , 317 , 333 , 334 , 350 , 361 ].…”

How have mathematical models contributed to understanding the transmission and control of SARS-CoV-2 in healthcare settings? A systematic search and review

“…All models exploring vaccination found that it could help reduce COVID-19 morbidity and mortality, especially in LTCFs [23,28,31,33,52,[63][64][65][66][67]. However, some studies also noted that vaccination benefits could be hindered by high levels of community SARS-CoV-2 circulation [31,65] or by reduced adherence to contact precautions within facilities concomitant with vaccine rollout, for instance due to pandemic fatigue or risk compensation [52].…”

“…The most universal finding is that more frequent testing leads to greater reductions in nosocomial transmission [12,14,21,23,24,[30][31][32][33][34][35][36][37][38][39][40]. Similarly, increasing daily testing capacity has been found to limit nosocomial transmission [27,41].…”

“…Conversely, staff vaccination was shown to be particularly effective for decreasing the overall attack rate, especially in the absence of a testing protocol [64]. Targeting staff for vaccination may also be preferable when the risk of virus importation from the community is high [31]. Finally, it has been shown that vaccine rollout should first target staff members most exposed to potential COVID-19 patients (e.g.…”

Quantifying the benefits of customized vaccination strategies: A network‐based optimization approach

“…Consequently, these efforts are hindered by the limitations of compartmental models and hence they are not able to incorporate subject‐specific risk and contact information. Given this, another stream of work, which has recently gained momentum, focuses on constructing more accurate agent‐based simulations that overcome these drawbacks (e.g., Faucher et al, 2022; Gomez Vazquez et al, 2022; Lee, Zabinsky, et al, 2022; Trad & El Falou, 2022). Although this line of work can provide valuable insights on the impact of certain policies on the disease dynamics, they unfortunately do not investigate the structure and composition of optimal vaccine distribution strategies.…”