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COVID-19 has posed an unprecedented global public health threat and caused a significant number of severe cases that necessitated long hospitalization and overwhelmed health services in the most affected countries. In response, governments initiated a series of non-pharmaceutical interventions (NPIs) that led to severe economic and social impacts. The effect of these intervention measures on the spread of the COVID-19 pandemic are not well investigated within developing country settings. This study simulated the trajectories of the COVID-19 pandemic curve in Jordan between February and May and assessed the effect of Jordan’s strict NPI measures on the spread of COVID-19. A modified susceptible, exposed, infected, and recovered (SEIR) epidemic model was utilized. The compartments in the proposed model categorized the Jordanian population into six deterministic compartments: suspected, exposed, infectious pre-symptomatic, infectious with mild symptoms, infectious with moderate to severe symptoms, and recovered. The GLEAMviz client simulator was used to run the simulation model. Epidemic curves were plotted for estimated COVID-19 cases in the simulation model, and compared against the reported cases. The simulation model estimated the highest number of total daily new COVID-19 cases, in the pre-symptomatic compartmental state, to be 65 cases, with an epidemic curve growing to its peak in 49 days and terminating in a duration of 83 days, and a total simulated cumulative case count of 1048 cases. The curve representing the number of actual reported cases in Jordan showed a good pattern compatibility to that in the mild and moderate to severe compartmental states. The reproduction number under the NPIs was reduced from 5.6 to less than one. NPIs in Jordan seem to be effective in controlling the COVID-19 epidemic and reducing the reproduction rate. Early strict intervention measures showed evidence of containing and suppressing the disease.

Background: The reproduction number (R 0 ) is vital in epidemiology to estimate the number of infected people and trace close contacts. R 0 values vary depending on social activity and type of gathering events that induce infection transmissibility and its pathophysiology dependence. Objectives: In this study, we estimated the probable outbreak size of COVID-19 clusters mathematically using a simple model that can predict the number of COVID-19 cases as a function of time. Methods: We proposed a mathematical model to estimate the R 0 of COVID-19 in an outbreak occurring in both local and international clusters in light of published data. Different types of clusters (religious, wedding, and industrial activity) were selected based on reported events in different countries between February and April 2020. Results: The highest R 0 values were found in wedding party events (5), followed by religious gathering events (2.5), while the lowest value was found in the industrial cluster (2). In return, this will enable us to assess the trend of coronavirus spread by comparing the model results and observed patterns. Conclusions: This study provides predictive COVID-19 transmission patterns in different cluster types based on different R 0 values. This model offers a contact-tracing task with the predicted number of cases, to decision-makers; this would help them in epidemiological investigations by knowing when to stop.

The aim of this study was to investigate the feasibility of refuse-derived fuel (RDF) production from municipal solid waste (MSW) generated in Jordan using a biodrying process for coprocessing in cement kilns in the region. At the end of the biodrying process, the mass of waste was reduced on average by approximately 35% when the dried waste was directed to the landfill without recovery of material. For RDF utilization of the dried waste, the mass of waste to be landfilled was reduced by approximately 69%. The RDF produced was of high calorific value, with low moisture and acceptable chlorine content (0.56–1.20% w/w) compared to the RDF produced in other countries. The quality of the produced RDF did not differ from the RDF quality set by some European countries. Concerning heavy metal concentrations, in all cases, they were lower than the reported ranges from the other countries considered. The biodrying process allowed an increase of about 58% in the waste calorific value (LHV) as a consequence of the waste moisture reduction. The calorific value of the produced RDF ranged from 14.83 to 15.58 MJ/kg, which made it suitable as a fuel. The findings showed that adding 15% RDF, equaling 4.92 tons/h, to the fuel used in cement kilns will save 486 USD/h in petcoke costs, with 2.27 tons/h of CO2 being emitted into the atmosphere at a net saving of 389 USD/h.