Does having a cat in your house increase your risk of catching COVID-19?

Multicriteria Risk Evaluation Model: Utilizing Fuzzy Logic for Improved Transparency and Quality of Risk Evaluation in Healthcare

Introduction

Risk management is essential for quality assurance in modern healthcare organizations. Risk matrices are widely used to evaluate risks in healthcare settings; however, this approach has noteworthy weaknesses and limitations. This paper introduces a novel risk evaluation model that utilizes multicriteria decision-making and fuzzy logic, to enhance the transparency and quality of the risk evaluation process in healthcare.

Methods

The Multicriteria Evaluation Model was developed using the Decision Expert method and expert knowledge integration. Fuzzy logic was integrated within the model, using partial degrees of membership and probabilistic analysis, to address uncertainties inherent to healthcare risk evaluation. The evaluation model was tested with healthcare professionals active in the field of risk management in clinical practice and compared with the risk matrix.

Results

The designed evaluation model utilizes multicriteria decision-making while encompassing the risk matrix framework to boost user understanding and enable meaningful comparison of results. Compared with the risk matrix, the model provided similar or marginally higher risk-level evaluations. The use of degrees of membership enables evaluators to articulate a wide range of plausible risk consequences, which are often overlooked or ambiguously addressed in the traditional risk matrix approach.

Discussion and Conclusions

The evaluation model demonstrates increased transparency of the decision-making process and facilitates in-depth analysis of the evaluation results. The utilization of degrees of membership revealed distinct strategies for handling uncertainty among participants, highlighting the weaknesses of using single value evaluation approach for the presented and similar decision problems. The presented approach is not limited to healthcare-related risk evaluation, but has the capacity to improve risk evaluation practices in diverse settings.

Seroprevalence of Anti-SARS-CoV-2 Antibodies in Cats during Five Waves of COVID-19 Epidemic in Thailand and Correlation with Human Outbreaks

Human-to-animal SARS-CoV-2 transmission was observed, including a veterinarian contracting COVID-19 through close contact with an infected cat, suggesting an atypical zoonotic transmission. This study investigated the prevalence of SARS-CoV-2 antibodies in cats during human outbreaks and elucidated the correlation between cat infections and human epidemics. A total of 1107 cat serum samples were collected and screened for SARS-CoV-2 antibodies using a modified indirect ELISA human SARS-CoV-2 antibody detection kit. The samples were confirmed using a cPass™ neutralization test. The SARS-CoV-2 seropositivity rate was 22.67% (199/878), mirroring the trend observed in concomitant human case numbers. The waves of the epidemic and the provinces did not significantly impact ELISA-positive cats. Notably, Chon Buri exhibited a strong positive correlation (r = 0.99, p = 0.009) between positive cat sera and reported human case numbers. Additionally, the cPass™ neutralization test revealed a 3.99% (35/878) seropositivity rate. There were significant differences in numbers and proportions of positive cat sera between epidemic waves. In Samut Sakhon, a positive correlation (r = 1, p = 0.042) was noted between the proportion of positive cat sera and human prevalence. The findings emphasize the need for ongoing surveillance to comprehend SARS-CoV-2 dynamics in both human and feline populations.

SARS-CoV-2 infection in dogs and cats is associated with contact to COVID-19-positive household members

Several domestic and wild animal species are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Reported (sero)prevalence in dogs and cats vary largely depending on the target population, test characteristics, geographical location and time period. This research assessed the prevalence of SARS-CoV-2-positive cats and dogs (PCR- and/or antibody positive) in two different populations. Dogs and cats living in a household with at least one confirmed COVID-19-positive person (household (HH) study; 156 dogs and 152 cats) and dogs and cats visiting a veterinary clinic (VC) (VC study; 183 dogs and 140 cats) were sampled and tested for presence of virus (PCR) and antibodies. Potential risk factors were evaluated and follow-up of PCR-positive animals was performed to determine the duration of virus shedding and to detect potential transmission between pets in the same HH. In the HH study, 18.8% (27 dogs, 31 cats) tested SARS-CoV-2 positive (PCR- and/or antibody positive), whereas in the VC study, SARS-CoV-2 prevalence was much lower (4.6%; six dogs, nine cats). SARS-CoV-2 prevalence amongst dogs and cats was significantly higher in the multi-person HHs with two or more COVID-19-positive persons compared with multi-person HHs with only one COVID-19-positive person. In both study populations, no associations could be identified between SARS-CoV-2 status of the animal and health status, age or sex. During follow-up of PCR-positive animals, no transmission to other pets in the HH was observed despite long-lasting virus shedding in cats (up to 35 days). SARS-CoV-2 infection in dogs and cats appeared to be clearly associated with reported COVID-19-positive status of the HH. Our study supports previous findings and suggests a very low risk of pet-to-human transmission within HHs, no severe clinical signs in pets and a negligible pet-to-pet transmission between HHs.