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1. Simulating the Mitigating Effects of Social Distancing and Vaccination during a Pandemic​

   https://doi.org/10.47611/jsrhs.v11i1.2490  

   Yang, Grant; Loewenberg, Michael; Lewis, Rostacia (February 2022, Journal of Student Research)

   Understanding the spread of a virus through a large population has always been important for mitigation, treatment, and prevention purposes. In the unprecedented wake of the COVID-19 (SARS-CoV-2) pandemic, techniques to understand and test preventative measures—like vaccination and quarantining—have become increasingly necessary. The developed compartmental model simulates the interactions between (N) people, with variable infection rates for vaccinated (alpha = 0.05) and unvaccinated (Beta = 0.25) people, as well as a (t = 15) day recovery from infection. Both the range of their infectivity, controlled by the quarantine variable (q), and the vaccination rate (f) of the population were varied. The main tests were on the variables of vaccine distribution and effectiveness, as well as quarantine range and the combination between the two. The results suggest that vaccination has a negative linear effect on infection cases over the course of the simulation, while quarantine has a minimal effect until higher amounts (over 80% quarantine), with the inverse being true for duration (increasing with stricter measures). Vaccination and quarantining also have a negative linear and exponential effect respectively on peak case count, which would be helpful in managing the patient flow into hospitals. Reproduction number was also found to be limited below 1.0 by vaccination measures, bringing the outbreak to an end. From these findings, it would be reasonable to suggest that vaccination is nearly ubiquitously helpful, while much stricter quarantine restrictions must be put in place for substantial effect, with the goal to flatten peak cases and decrease reproduction number. 

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2. Bayesian Inference for COVID-19 Transmission Dynamics in India Using a Modified SEIR Model

   https://doi.org/10.3390/math10214037  

   Yin, Kai; Mondal, Anirban; Ndeffo-Mbah, Martial; Banerjee, Paromita; Huang, Qimin; Gurarie, David (November 2022, Mathematics)

   We propose a modified population-based susceptible-exposed-infectious-recovered (SEIR) compartmental model for a retrospective study of the COVID-19 transmission dynamics in India during the first wave. We extend the conventional SEIR methodology to account for the complexities of COVID-19 infection, its multiple symptoms, and transmission pathways. In particular, we consider a time-dependent transmission rate to account for governmental controls (e.g., national lockdown) and individual behavioral factors (e.g., social distancing, mask-wearing, personal hygiene, and self-quarantine). An essential feature of COVID-19 that is different from other infections is the significant contribution of asymptomatic and pre-symptomatic cases to the transmission cycle. A Bayesian method is used to calibrate the proposed SEIR model using publicly available data (daily new tested positive, death, and recovery cases) from several Indian states. The uncertainty of the parameters is naturally expressed as the posterior probability distribution. The calibrated model is used to estimate undetected cases and study different initial intervention policies, screening rates, and public behavior factors, that can potentially strike a balance between disease control and the humanitarian crisis caused by a sudden strict lockdown. 

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3. Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity

   https://doi.org/10.1073/pnas.2019716118  

   Subramanian, Rahul; He, Qixin; Pascual, Mercedes (February 2021, Proceedings of the National Academy of Sciences)

   null (Ed.)

   The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13 to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with presymptomatic ones. If asymptomatic infections transmit at similar rates as symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, presymptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection subpopulations have reproductive numbers lower than three. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) should be reconsidered. 

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4. Multilayer network analysis of FMD transmission and containment among beef cattle farms

   https://doi.org/10.1038/s41598-022-19981-0  

   Yi, Chunlin; Yang, Qihui; Scoglio, Caterina M. (December 2022, Scientific Reports)

   Abstract As a highly contagious livestock viral disease, foot-and-mouth disease poses a great threat to the beef-cattle industry. Direct animal movement is always considered as a major route for between-farm transmission of FMD virus. Sharing contaminated equipment and vehicles have also attracted increasing interests as an indirect but considerable route for FMD virus transmission. With the rapid development of communication technologies, information-sharing techniques have been used to control epidemics. In this paper, we built farm-level time-series three-layer networks to simulate the between-farm FMD virus transmission in southwest Kansas by cattle movements (direct-contact layer) and truck visits (indirect-contact layer) and evaluate the impact of information-sharing techniques (information-sharing layer) on mitigating the epidemic. Here, the information-sharing network is defined as the structure that enables the quarantine of farms that are connected with infected farms. When a farm is infected, its infection status is shared with the neighboring farms in the information-sharing network, which in turn become quarantined. The results show that truck visits can enlarge the epidemic size and prolong the epidemic duration of the FMD outbreak by cattle movements, and that the information-sharing technique is able to mitigate the epidemic. The mitigation effect of the information-sharing network varies with the information-sharing network topology and different participation levels. In general, an increased participation leads to a decreased epidemic size and an increased quarantine size. We compared the mitigation performance of three different information-sharing networks (random network, contact-based network, and distance-based network) and found the outbreak on the network with contact-based information-sharing layer has the smallest epidemic size under almost any participation level and smallest quarantine size with high participation. Furthermore, we explored the potential economic loss from the infection and the quarantine. By varying the ratio of the average loss of quarantine to the loss of infection, we found high participation results in reduced economic losses under the realistic assumption that culling costs are much greater than quarantine costs. 

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5. Spatiotemporal Patterns of COVID-19 Impact on Human Activities and Environment in Mainland China Using Nighttime Light and Air Quality Data

   https://doi.org/10.3390/rs12101576  

   Liu, Qian; Sha, Dexuan; Liu, Wei; Houser, Paul; Zhang, Luyao; Hou, Ruizhi; Lan, Hai; Flynn, Colin; Lu, Mingyue; Hu, Tao; et al (May 2020, Remote Sensing)

   null (Ed.)

   The sudden outbreak of the COVID-19 pandemic has brought drastic changes to people’s daily lives, work, and the surrounding environment. Investigations into these changes are very important for decision makers to implement policies on economic loss assessments and stimulation packages, city reopening, resilience of the environment, and arrangement of medical resources. In order to analyze the impact of COVID-19 on people’s lives, activities, and the natural environment, this paper investigates the spatial and temporal characteristics of Nighttime Light (NTL) radiance and Air Quality Index (AQI) before and during the pandemic in mainland China. The monthly mean NTL radiance, and daily and monthly mean AQI are calculated over mainland China and compared before and during the pandemic. Our results show that the monthly average NTL brightness is much lower during the quarantine period than before. This study categorizes NTL into three classes: residential area, transportation, and public facilities and commercial centers, with NTL radiance ranges of 5–20, 20–40 and greater than 40 (nW· cm − 2 · sr − 1 ), respectively. We found that the Number of Pixels (NOP) with NTL detection increased in the residential area and decreased in the commercial centers for most of the provinces after the shutdown, while transportation and public facilities generally stayed the same. More specifically, we examined these factors in Wuhan, where the first confirmed cases were reported, and where the earliest quarantine measures were taken. Observations and analysis of pixels associated with commercial centers were observed to have lower NTL radiance values, indicating a dimming behavior, while residential area pixels recorded increased levels of brightness after the beginning of the lockdown. The study also discovered a significant decreasing trend in the daily average AQI for mainland China from January to March 2020, with cleaner air in most provinces during February and March, compared to January 2020. In conclusion, the outbreak and spread of COVID-19 has had a crucial impact on people’s daily lives and activity ranges through the increased implementation of lockdown and quarantine policies. On the other hand, the air quality of mainland China has improved with the reduction in non-essential industries and motor vehicle usage. This evidence demonstrates that the Chinese government has executed very stringent quarantine policies to deal with the pandemic. The decisive response to control the spread of COVID-19 provides a reference for other parts of the world. 

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