Optimal Treatment Strategy for Infectious Diseases with Two Treatment Stages

In this paper, a disease transmission model with two treatment stages is proposed and analyzed. The results indicate that the basic reproduction number is a critical threshold for the prevalence of the disease. If the basic reproduction number is less than one, the disease free equilibrium is globally asymptotically stable. Otherwise, the endemic equilibrium is globally asymptotically stable. Therefore, besides the basic reproduction number, a new marker for characterizing the seriousness of the disease, named as dynamical final infective size, is proposed, which differs from traditional final size because the proposed model includes the natural birth and death. Finally, optimization strategies for limited medical resources are obtained from the perspectives of basic reproduction number and dynamical final infective size, and the real-world disease management scenarios are given based on these finding.

A Study into Digital Dermatitis Transmission and Bacterial Associated Pathological Changes Involved in the Disease

Digital dermatitis is a highly prevalent painful lesion affecting the feet in dairy cattle. Even though the pathogenesis has been subject of investigation since 1974, there is still a lack of knowledge about the spread of the disease among cows within a herd as well as between herds. The purpose of this study was to monitor transmission of digital dermatitis under experimental conditions between naive heifers and affected animals, to monitor the changes in clinical appearance, microbial colonisation of the skin as lesions progressed and to apply a q-PCR for the detection of Treponema spp. in faecal samples. Eight heifers with clinical normal digital skin were housed with 5 heifers with severe digital dermatitis lesion for 8 weeks on a solid concrete floor with an accumulating layer of slurry. Digital skin was examined daily and lesions were clinically scored. Skin biopsies were taken from the healthy heifers at introduction and weekly from all lesions for histopathological evaluation and fluorescence in situ hybridization. None of the healthy heifers developed digital dermatitis and in 4 out of 5 infected heifers the lesions healed during the study. All samples from healthy skin were negative for Treponema spp. and one sample were positive for Dichelobacter nodosus. Colonization of healthy skin could not be identified in this study. There was no significant relation between clinical scoring of the lesions and histopathological score and the presence of Treponema spp. There were however a significant relation between the prevalence of Treponema spp. in the skin and severity of changes in epidermis and dermis. By qPCR all the healthy heifers were found to excrete Treponema spp. in their faeces.

Fuzzy Based Decision Making Approach for Evaluating the Severity of COVID-19 Pandemic in Cities of Kingdom of Saudi Arabia

The World Health Organization declared COVID-19 a pandemic on March 11,2020 stating that it is a worldwide danger and requires imminent preventive strategies to minimise the loss of lives.COVID-19 has now affected millions across 211 countries in the world and the numbers continue to rise.The information discharged by the WHO till June 15,2020 reports 8,063,990 cases of COVID-19.As the world thinks about the lethal malady for which there is yet no immunization or a predefined course of drug,the nations are relentlessly working at the most ideal preventive systems to contain the infection.The Kingdom of Saudi Arabia(KSA)is additionally combating with the COVID-19 danger as the cases announced till June 15,2020 reached the count of 132,048 with 1,011 deaths.According to the report released by the KSA on June 14,2020,more than 4,000 cases of COVID-19 pandemic had been registered in the country.Tending to the impending requirement for successful preventive instruments to stem the fatalities caused by the disease,our examination expects to assess the severity of COVID-19 pandemic in cities of KSA.In addition,computational model for evaluating the severity of COVID-19 with the perspective of social influence factor is necessary for controlling the disease.Furthermore,a quantitative evaluation of severity associated with specific regions and cities of KSA would be a more effective reference for the healthcare sector in Saudi Arabia.Further,this paper has taken the Fuzzy Analytic Hierarchy Process(AHP)technique for quantitatively assessing the severity of COVID-19 pandemic in cities of KSA.The discoveries and the proposed structure would be a practical,expeditious and exceptionally precise evaluation system for assessing the severity of the pandemic in the cities of KSA.Hence these urban zones clearly emerge as the COVID-19 hotspots.The cities require suggestive measures of health organizations that must be introduced on a war footing basis to counter the pandemic.The analysis tabulated in our study will assist in mapping the rules and building a systematic structure that is immediate need in the cities with high severity levels due to the pandemic.

Analyzing the Implications of COVID-19 Pandemic through an Intelligent-Computing Technique

The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the WorldHealth Organization (WHO) on March 11, 2020. COVID-19 has already affectedmore than 211 nations. In such a bleak scenario, it becomes imperative to analyzeand identify those regions in Saudi Arabia that are at high risk. A preemptivestudy done in the context of predicting the possible COVID-19 hotspots wouldfacilitate in the implementation of prompt and targeted countermeasures againstSARS-CoV-2, thus saving many lives. Working towards this intent, the presentstudy adopts a decision making based methodology of simulation named Analytical Hierarchy Process (AHP), a multi criteria decision making approach, forassessing the risk of COVID-19 in different regions of Saudi Arabia. AHP givesthe ability to measure the risks numerically. Moreover, numerical assessments arealways effective and easy to understand. Hence, this research endeavour employsFuzzy based computational method of decision making for its empirical analysis.Findings in the proposed paper suggest that Riyadh and Makkah are the mostsusceptible regions, implying that if sustained and focused preventive measuresare not introduced at the right juncture, the two cities could be the worst afflictedwith the infection. The results obtained through Fuzzy based computationalmethod of decision making are highly corroborative and would be very usefulfor categorizing and assessing the current COVID-19 situation in the Kingdomof Saudi Arabia. More specifically, identifying the cities that are likely to beCOVID-19 hotspots would help the country’s health and medical fraternity toreinforce intensive containment strategies to counter the ills of the pandemic insuch regions.

Epidemic spreading behavior with time delay on local-world evolving networks

An improved susceptible-infected-susceptible(SIS)model in the local-world evolving network model is presented to study the epidemic spreading behavior with time delay,which is added into the infected phase.The local-world evolving model displays a transition from the exponential network to the scale-free network with respect to the degree distribution.Two typical delay regimes,i.e.,uniform and degree-dependent delays are incorporated into the SIS epidemic model to investigate the epidemic infection processes in the local-world net-work model.The results indicate that the infection delay will promote the epidemic outbreaks,increase the prevalence and reduce the critical threshold of epidemic spreading.It is also found that local-world size M will considerably influence the epidemic spreading behavior with time delay in the local-world network through large-scale numerical simulations.Simulation results are also of relevance to fight epidemic outbreaks.