ABSTRACT
A deterministic S,Em,Ec,Im,Ic,H,R epidemic model that describes the spreading of SARS-COV-2 within a community with comorbidities is formulated. Size dependent area is incorporated into the model to quantify the effect of social distancing and the results indicate that the risk of community transmission is optimumly minimised when the occupancy area is increased. The reproduction number is shown to have a positive relationship with the infection rate, the proportion of individuals with comorbidities and the proportion of susceptible individuals adhering to standard operating procedures. The model exhibits a unique endemic equilibrium whose stability largely depends on the rate of hospitalisation of individuals with underlying health conditions (ωm) as compared to those without these conditions (ωc), such that stability is guaranteed if ωm<ωc. Furthermore, if individuals with comorbidities effectively report for treatment and hospitalisation at a rate of 0.5 per day, the epidemic curve peaks 3-fold higher among people with comorbidities. The infection peaks are delayed if the area occupied by community is increased. In conclusion, we observed that community infections increase significantly with decreasing detection rates for both individuals with or without comorbidities.
ABSTRACT
Background: Uganda has a unique set up comprised of resource-constrained economy, social-economic challenges, politically diverse regional neighborhood and home to long-standing refuge crisis that comes from long and protracted conflicts of the great lakes. The devastation of the on-going global pandemic outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is likely to be escalated by these circumstances with expectations of the impact of the disease being severe. Materials and methods: In this study, we formulate a mathematical model that incorporates the currently known disease characteristics and tracks various intervention measures that the government of Uganda has implemented since the reporting of the first case in March 2020. We then evaluate these measures to understand levels of responsiveness and adherence to standard operating procedures and quantify their impact on the disease burden. Novel in this model was the unique aspect of modeling the trace-and-isolate protocol in which some of the latently infected individuals tested positive while in strict isolation centers thereby reducing their infectious period.
ABSTRACT
This paper develops and analyses a habitat area size dependent mathematical model to study the transmission dynamics of COVID-19 in crowded settlements such as refugee camps, schools, markets and churches. The model quantifies the potential impact of physical/social distancing and population density on the disease burden. Results reveal that with no fatalities and no infected entrants, the reproduction numbers associated with asymptomatic and symptomatic cases are inversely proportional to; the habitat area size, and the efforts employed in tracing and hospitalising these cases. The critical habitat area below which the disease dies out is directly proportion to the time taken to identify and hospitalise infected individuals. Results also show that disease persistence in the community is guaranteed even with minimal admission of infected individuals. Our results further show that as the level of compliance to standard operating procedures (SOPs) increases, then the disease prevalence peaks are greatly reduced and delayed. Therefore, proper adherence to SOPs such as use of masks, physical distancing measures and effective contact tracing should be highly enforced in crowded settings if COVID-19 is to be mitigated.