matOptimize: A parallel tree optimization method enables online phylogenetics for SARS-CoV-2

Phylogenetic tree optimization is necessary for precise analysis of evolutionary and transmission dynamics, but existing tools are inadequate for handling the scale and pace of data produced during the COVID-19 pandemic. One transformative approach, online phylogenetics, aims to incrementally add samples to an ever-growing phylogeny, but there are no previously-existing approaches that can efficiently optimize this vast phylogeny under the time constraints of the pandemic. Here, we present matOptimize, a fast and memory-efficient phylogenetic tree optimization tool based on parsimony that can be parallelized across multiple CPU threads and nodes, and provides orders of magnitude improvement in runtime and peak memory usage compared to existing state-of-the-art methods. We have developed this method particularly to address the pressing need during the COVID-19 pandemic for daily maintenance and optimization of a comprehensive SARS-CoV-2 phylogeny. Thus, our approach addresses an important need for daily maintenance and refinement of a comprehensive SARS-CoV-2 phylogeny.

Mathematical Model and Analysis of Corruption Dynamics with Optimal Control

In this study, a deterministic mathematical model that explains the transmission dynamics of corruption is proposed and analyzed by considering social influence on honest individuals. Positivity and boundedness of solution of the model are proved and basic reproduction number R 0 is computed using the next-generation matrix method. The analysis shows that corruption-free equilibrium is locally and globally asymptotically stable whenever R 0 < 1 . Also, the endemic equilibrium point is locally and globally asymptotically stable whenever R 0 > 1 . Then, the model was extended to optimal control, and some numerical simulations with and without optimal control are also performed to verify the theoretical analysis using MATLAB. Numerical simulation of optimal control model shows that the prevention and punishment strategy is the most effective strategy to reduce the dynamic transmission of corruption.

SARS-CoV-2 Reverse Zoonoses to Pumas and Lions, South Africa

Reverse-zoonotic infections of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) from humans to wildlife species internationally raise concern over the emergence of new variants in animals. A better understanding of the transmission dynamics and pathogenesis in susceptible species will mitigate the risk to humans and wildlife occurring in Africa. Here we report infection of an exotic puma (July 2020) and three African lions (July 2021) in the same private zoo in Johannesburg, South Africa. One Health genomic surveillance identified transmission of a Delta variant from a zookeeper to the three lions, similar to those circulating in humans in South Africa. One lion developed pneumonia while the other cases had mild infection. Both the puma and lions remained positive for SARS-CoV-2 RNA for up to 7 weeks.

Integration of fuzzy logic in the SEIRD compartmental model for the analysis of intervention and transmission heterogeneity on SARS-CoV-2 transmission dynamics

Different epidemiological compartmental models have been presented to predict the transmission dynamics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we have proposed a fuzzy rule-based Susceptible-Exposed-Infectious-Recovered-Death ([Formula: see text]) compartmental model considering a new dynamic transmission possibility variable as a function of time and three different fuzzy linguistic intervention variables to delineate the intervention and transmission heterogeneity on SARS-CoV-2 viral infection. We have analyzed the datasets of active cases and total death cases of China and Bangladesh. Using our model, we have predicted active cases and total death cases for China and Bangladesh. We further presented the correspondence of different intervention measures in relaxing the transmission possibility. The proposed model delineates the correspondence between the intervention measures as fuzzy subsets and the predicted active cases and total death cases. The prediction made by our system fitted the collected dataset very well while considering different fuzzy intervention measures. The integration of fuzzy logic in the classical compartmental model also produces more realistic results as it generates a dynamic transmission possibility variable. The proposed model could be used to control the transmission of SARS-CoV-2 as it deals with the intervention and transmission heterogeneity on SARS-CoV-2 transmission dynamics.

Public Health Policy Pillars for the Sustainable Elimination of Zoonotic Schistosomiasis

Schistosomiasis is a parasitic disease acquired through contact with contaminated freshwater. The definitive hosts are terrestrial mammals, including humans, with some Schistosoma species crossing the animal-human boundary through zoonotic transmission. An estimated 12 million people live at risk of zoonotic schistosomiasis caused by Schistosoma japonicum and Schistosoma mekongi, largely in the World Health Organization&rsquo;s Western Pacific Region and in Indonesia. Mathematical models have played a vital role in our understanding of the biology, transmission, and impact of intervention strategies, however, these have mostly focused on non-zoonotic Schistosoma species. Whilst these non-zoonotic-based models capture some aspects of zoonotic schistosomiasis transmission dynamics, the commonly-used frameworks are yet to adequately capture the complex epi-ecology of multi-host zoonotic transmission. However, overcoming these knowledge gaps goes beyond transmission dynamics modelling. To improve model utility and enhance zoonotic schistosomiasis control programmes, we highlight three pillars that we believe are vital to sustainable interventions at the implementation (community) and policy-level, and discuss the pillars in the context of a One-Health approach, recognising the interconnection between humans, animals and their shared environment. These pillars are: (1) human and animal epi-ecological understanding; (2) economic considerations (such as treatment costs and animal losses); and (3) sociological understanding, including inter- and intra-human and animal interactions.

Application of Mathematical Modeling in Prediction of COVID-19 Transmission Dynamics

The entire world has been affected by the outbreak of COVID-19 since early 2020. Human carriers are largely the spreaders of this new disease, and it spreads much faster compared to previously identified coronaviruses and other flu viruses. Although vaccines have been invented and released, it will still be a challenge to overcome this disease. To save lives, it is important to better understand how the virus is transmitted from one host to another and how future areas of infection can be predicted. Recently, the second wave of infection has hit multiple countries, and governments have implemented necessary measures to tackle the spread of the virus. We investigated the three phases of COVID-19 research through a selected list of mathematical modeling articles. To take the necessary measures, it is important to understand the transmission dynamics of the disease, and mathematical modeling has been considered a proven technique in predicting such dynamics. To this end, this paper summarizes all the available mathematical models that have been used in predicting the transmission of COVID-19. A total of nine mathematical models have been thoroughly reviewed and characterized in this work, so as to understand the intrinsic properties of each model in predicting disease transmission dynamics. The application of these nine models in predicting COVID-19 transmission dynamics is presented with a case study, along with detailed comparisons of these models. Toward the end of the paper, key behavioral properties of each model, relevant challenges and future directions are discussed.

A review of COVID-19 transmission dynamics and clinical outcomes on cruise ships worldwide, January to October 2020

Background Cruise ships provide an ideal setting for transmission of SARS-CoV-2, given the socially dense exposure environment. Aim To provide a comprehensive review of COVID-19 outbreaks on cruise ships. Methods PubMed was searched for COVID-19 cases associated with cruise ships between January and October 2020. A list of cruise ships with COVID-19 was cross-referenced with the United States Centers for Disease Control and Prevention’s list of cruise ships associated with a COVID-19 case within 14 days of disembarkation. News articles were also searched for epidemiological information. Narratives of COVID-19 outbreaks on ships with over 100 cases are presented. Results Seventy-nine ships and 104 unique voyages were associated with COVID-19 cases before 1 October 2020. Nineteen ships had more than one voyage with a case of COVID-19. The median number of cases per ship was three (interquartile range (IQR): 1–17.8), with two notable outliers: the Diamond Princess and the Ruby Princess, which had 712 and 907 cases, respectively. The median attack rate for COVID-19 was 0.2% (IQR: 0.03–1.5), although this distribution was right-skewed with a mean attack rate of 3.7%; 25.9% (27/104) of voyages had at least one COVID-19-associated death. Outbreaks involving only crew occurred later than outbreaks involving guests and crew. Conclusions In the absence of mitigation measures, COVID-19 can spread easily on cruise ships in a susceptible population because of the confined space and high-density contact networks. This environment can create superspreader events and facilitate international spread.