Precautionary Action Research Articles

Heavy metal concentrations in the edible portions of Centella asiatica: Health risk toward chronic kidney disease of uncertain etiology

Centella asiatica is a commonly consumed green leafy vegetable in many developing countries due its high nutritious value and availability at low cost. The present study was conducted to assess the Cd, Cr and Pb uptake associated health risks of Centella asiatica harvested from organic and non-organic cultivations in a chronic kidney disease of uncertain etiology (CKDue) prevalent area in Sri Lanka. The health risk assessment was conducted in terms of the bioconcentration factor (BCF), soil-to-root and root-to-leaf translocation factors ({text{TF}},({text{soil-root}}) and {text{TF}},({text{root-leaf}})), Target hazard quotient for each heavy metal (THQ) and hazard index (HI). In addition, the spatial variation of physical and chemical parameters of the root zone soil were assessed using MINITAB 17 statistical software. Results indicated significant spatial variations in conductivity, organic matter content and Cr concentrations among organic and non-organic study sites. The Cr, Cd and Pb concentrations recorded from roots and leaves of Centella asiatica were higher than the safe limits for consumption established by the European Union. The health risk analysis indicated that there is a potential of hyper-accumulating Cd in the roots of Centella asiatica. Further, the THQ and HI of the heavy metals indicated possible adverse non-cancer health risks associated with long-term consumption of leaves of Centella asiatica. Therefore, necessary precautionary actions to prevent the excessive buildup of Cr, Cd and Pb in the edible portions of Centella asiatica are essential in order to ensure consumer safety.

A knowledge-based self-pre-diagnosis system to predict Covid-19 in smartphone users using personal data and observed symptoms.

Covid‐19 is an acute respiratory infection and presents various clinical features ranging from no symptoms to severe pneumonia and death. Medical expert systems, especially in diagnosis and monitoring stages, can give positive consequences in the struggle against Covid‐19. In this study, a rule‐based expert system is designed as a predictive tool in self‐pre‐diagnosis of Covid‐19. The potential users are smartphone users, healthcare experts and government health authorities. The system does not only share the data gathered from the users with experts, but also analyzes the symptom data as a diagnostic assistant to predict possible Covid‐19 risk. To do this, a user needs to fill out a patient examination card that conducts an online Covid‐19 diagnostic test, to receive an unconfirmed online test prediction result and a set of precautionary and supportive action suggestions. The system was tested for 169 positive cases. The results produced by the system were compared with the real PCR test results for the same cases. For patients with certain symptomatic findings, there was no significant difference found between the results of the system and the confirmed test results with PCR test. Furthermore, a set of suitable suggestions produced by the system were compared with the written suggestions of a collaborated health expert. The suggestions deduced and the written suggestions of the health expert were similar and the system suggestions in line with suggestions of the expert. The system can be suitable for diagnosing and monitoring of positive cases in the areas other than clinics and hospitals during the Covid‐19 pandemic. The results of the case studies are promising, and it demonstrates the applicability, effectiveness, and efficiency of the proposed approach in all communities.

Non-linear effects of absolute risk information on individuals’self-evaluation, affective responses, and behavioral intentionsof precautionary actions against skin cancer

Objective The current study explores non-linear effects of absolute risk and effects of comparative risk information about skin cancer on individuals’ safety ratings, affective responses and behavioral intentions. Method An experimental survey was conducted among college students (N = 563) to test the effects of absolute and comparative risk information across a range of risk levels from 3.7% to 60%. Results The non-linear model of absolute risk effect was confirmed by the data. Absolute risk information had detectable effects at low levels of risk, but the effects did not change appreciably at the highest absolute risk levels. Regarding comparative risk, the data did not support its effects on individuals’ safety ratings, affective responses and behavioral intentions. Conclusion The study found the non-linear model fits well to the skin cancer related feelings and behavioral intentions. It suggests future research apply non-linear models to a variety of health communication areas.

Are countries’ precautionary actions against COVID-19 effective? An assessment study of 175 countries worldwide

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has affected many countries negatively, particularly in terms of their health care and financial systems. Numerous countries have attempted to employ precautions to address this pandemic. This study was aimed at exploring and assessing the early precautionary actions taken by 175 countries on six continents to prevent the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). MethodsAn observational study utilizing available public data was conducted on the basis of data collected from December 31, 2019 until the end of April 2020 and then compared with data in January 2021. Several data were extracted, including information related to the date of the first reported case of SARS-CoV-2, total confirmed cases, total active cases and more. In addition, seven validated indicators were used to assess the countries’ preparedness and precautionary actions. ResultsA total of 175 countries were included in the study. The total COVID-19 infection rate increased exponentially and rapidly in North America and Europe from March to April. The application of precautions (indicators) varied between countries. School closures, quarantines and curfews were the most-applied indicators among all countries. As for the relationship between the indicators and their effects on the infection rate, Italy and Spain were the top countries in Europe and adopted all the indicators. Nevertheless, they faced high infection rates: 239,639 and 205,463 COVID-19 cases in Spain and Italy, respectively. ConclusionThe precautionary actions might have played a role in limiting the spread of COVID-19 in several countries. However, many countries might not benefit from applying these indicators.

An EEMD-BiLSTM Algorithm Integrated with Boruta Random Forest Optimiser for Significant Wave Height Forecasting along Coastal Areas of Queensland, Australia

Using advanced deep learning (DL) algorithms for forecasting significant wave height of coastal sea waves over a relatively short period can generate important information on its impact and behaviour. This is vital for prior planning and decision making for events such as search and rescue and wave surges along the coastal environment. Short-term 24 h forecasting could provide adequate time for relevant groups to take precautionary action. This study uses features of ocean waves such as zero up crossing wave period (Tz), peak energy wave period (Tp), sea surface temperature (SST) and significant lags for significant wave height (Hs) forecasting. The dataset was collected from 2014 to 2019 at 30 min intervals along the coastal regions of major cities in Queensland, Australia. The novelty of this study is the development and application of a highly accurate hybrid Boruta random forest (BRF)–ensemble empirical mode decomposition (EEMD)–bidirectional long short-term memory (BiLSTM) algorithm to predict significant wave height (Hs). The EEMD–BiLSTM model outperforms all other models with a higher Pearson’s correlation (R) value of 0.9961 (BiLSTM—0.991, EEMD-support vector regression (SVR)—0.9852, SVR—0.9801) and comparatively lower relative mean square error (RMSE) of 0.0214 (BiLSTM—0.0248, EEMD-SVR—0.043, SVR—0.0507) for Cairns and similarly a higher Pearson’s correlation (R) value of 0.9965 (BiLSTM—0.9903, EEMD–SVR—0.9953, SVR—0.9935) and comparatively lower RMSE of 0.0413 (BiLSTM—0.075, EEMD-SVR—0.0481, SVR—0.057) for Gold Coast.

Effects of News and Threat Perceptions on Americans’ COVID-19 Precautionary Behaviors

Our study examines the relationship between news exposure at the onset of the COVID-19 pandemic, personal threat beliefs, beliefs about others’ threat perceptions, and participation in precautionary actions. A survey of 377 U.S . adults revealed a significant main effect of news exposure on various precautionary behaviors (e.g., facial mask wear, physical distancing). Personal threat beliefs and beliefs about others’ threat perceptions serve as unique mechanisms mediating the effect of news on specific CDC-recommended and less socially desirable actions. These findings can guide news sources covering health crises in a socially responsible manner.

Characterization of soil phosphate status, sorption and saturation in paddy wetlands in usangu basin-Tanzania

Phosphorus (P) is a vital plant macronutrient required for plant growth which usually available in limited amount. P availability for plant uptake in highly weathered soil is controlled by soil erosion and high fixation. The availability of P applied from fertilizers depend on the soil pH, soil sorption capacity (PSC) and P saturation status (PSD), which determines P storage, losses, fixation, and additional P to be added with minimal loss to the environment. PSC and PSD are agro-environmental indicators used to estimate P availability and P loss to the environment. However, PSC and PSD of agricultural soils had been never studied in Tanzanian soils. This study was conducted to assess and estimate P availability, PSC and PSD and the risks of P losses in tropical soils from Usangu basin popular for paddy farming. In total, 198 soil samples from 10 paddy irrigation schemes were collected (November–December 2019) and analyzed for inherent P (PM3), metal oxides of Aluminium (Al M3), iron (Fe M3), and calcium (Ca M3) as main PSC and PSD determinant. The determined concentrations were in range of; P M3 014.9–974.69 mg/kg, Al M3 234.56–3789.36 mg/kg, Fe M3 456.78–2980.23 mg/kg, and Ca M3 234.67–973.34 mg/kg. Estimated PSCM3 ranged 5.62–34.85 mmol/kg with a mean value of 14.14 mmol/kg corresponding to high status, ensuring high P holding capacity for plant uptake. However, some soils had very low PSCM3 creating a risk of P loss to environment. Among soils, the estimated PSD M3 ranged from 0.01 to 17.57% and was below (<24%), indicating low P loss risks to surface and groundwater, however, some soils were observed to have PSDM3 above 15% which correspond to a critical degree of phosphate saturation of 25% in a watershed using oxalate extraction method. Therefore some sites were associated with high P loss to the environment, immediate and precautionary actions for sustainable P management to increase productivity, environmental safety and sustainability are needed to be in place.

Public precaution awareness: a case study from Google search trend during Covid-19 outbreak in Indonesia

Objective: The global outbreak of COVID-19 is emerged recently and this poses stress on health and well-being of the people in the worldwide including in Indonesia. Public interest in this new issue largely reflects people’s attention to COVID-19 and their willingness to take precautionary actions. This study aimed to examine public awareness on the prevention of COVID-19 using Google Trend (GT) . Methods: Using GT, we retrieved public query data for the term of (coronavirus, handwashing, hand sanitizer and facemask) between 12 December 2019 and 4 April 2020 in the specific locations of Indonesia nationwide and several provinces. The correlation between daily search volumes on the topic related to COVID-19 and the daily number of people infected with COVID-19 was analyzed. Results: Our studies observed the overall search trend of RSV regarding COVID-19 after the global outbreak and the announcement of first covid-19 case in Indonesia, the search related to COVID-19, and other defined terms in Indonesia increased rapidly. In addition, search related to face mask were gradually increased. Searches for face mask and hand sanitizer is more popular than handwashing. There is a positive correlation between daily RSV on COVID-19 and other defined terms and the daily number of people infected with COVID-19 nationwide ( p <0·05). There are various interest to RSV related to COVID-19, and public awareness of COVID-19 was almost similar in some provinces, particularly searches related to facemask and hand sanitizer. Conclusion: Our findings demonstrates that GT could potentially define the proper timing and location for practicing appropriate risk communication strategies to prevent the spread of emerging disease. The study demonstrates that government should strengthen the publicity of COVID- 19 nationally, reinforce the public's awareness on the prevention of COVID-19 and finally inform the importance of protecting individuals with appropriate and affordable precautionary measures.

Knowledge, precautionary actions, and perceived risk of COVID-19 among Indonesian people

Novel coronavirus was first identified in China in December 2019, causing several cases of the new type of pneumonia. The exported cases were found in other countries, including countries in the Southeast Asia region. At the same time, no cases were confirmed in Indonesia. We aimed to assess COVID-19 related knowledge, precautionary actions, and perceived risk among general Indonesian population when there were no confirmed cases in Indonesia. This study was a descriptive cross-sectional study involving 382 participants aged 17 years and above residing in Indonesia. The data was collected through the online questionnaire from February 19&lt;sup&gt;th &lt;/sup&gt;to February 29&lt;sup&gt;th&lt;/sup&gt; 2020. The average score of COVID-19 related knowledge was 88.0%, whereas 83.8% of the participants had a high level of knowledge. The average score of taking precautionary actions was 77.4% and 65.7% had a high level of performance. In terms of the perceived risk of COVID-19, only 11.3% of the participants perceived themselves likely to acquire COVID-19 when compared with other diseases or accidents. The perceived risk of COVID-19 was significantly associated with precautionary action (p&amp;lt;0.05). Perceived risk of COVID-19 was at a low level when there were no confirmed cases. Effective strategies of risk communication are needed to improve precautionary actions to prevent COVID-19.

Perceived Risk of COVID-19 and Related Factors Among University Students in Ethiopia During School Reopening.

BackgroundThe novel coronavirus disease 2019 (COVID-19) has posed a great threat to the public. University students living in school compound with groups and sharing a common cafeteria are more susceptible to contract and spread the virus. Risk perception multiplies fear and anxiety that triggers precautionary action. However, research is scant in this particular field.ObjectiveTo assess the perceived risk of COVID-19 and its associated factors among University Students in Northeast Ethiopia during school reopening.MethodsInstitution-based cross-sectional study was conducted among 682 Debre Berhan University students from December 1–15, 2020, when students just get back to school. Data was collected using a structured and pre-tested questionnaire. A multistage sampling technique was used to select study subjects. Data were cleaned and entered into Epi-Data version 4.6 and exported to SPSS version 25 software for analysis. Descriptive statistics, bivariable and multivariable logistic regression analysis were run to summarize the results.ResultsThe overall perceived risk of COVID-19 was 296 (43.4%), 95% CI (39.4–47.4). Age (AOR (CI) =3.27 (1.87–5.71), open relationship (AOR (CI) =3.17 (1.73–5.79), fathers’ education (AOR (CI) =2.29 (1.31–4.02), having diabetes (AOR (CI) =2.64 (1.15–6.07), and information source from ministry of health (MOH) (AOR (CI) =1.87 (1.27–2.75) had significantly high-risk perception. However, students who use Facebook (AOR (CI) =0.57 (0.39–0.82) and Websites/articles (AOR (CI) =0.14 (0.06–0.34) had significantly low-risk perception. Television (59.8%) and Telegram (66.6%) were the primary sources of information, while the World Health Organization (68.3%) was the most trusted source of information.ConclusionUniversity students perceived a low risk towards COVID-19 pandemics at the time of school resumption. It was influenced by students’ demographic characteristics, co-morbidities, social media, and information sources. The Ministry of Health and Ministry of Education should properly promote risk communication among university students.

Decadal and multidecadal natural variability of African rainfall

Study regionAfrica Study focusAfrican rainfall shows significant year-to-year natural fluctuations that in part are linked to teleconnections associated with modes of variability in the Atlantic, Pacific and Indian oceans. A better understanding of African rainfall variability and potential drivers would help to better prepare African societies for anticipated droughts and floods by taking early precautionary action. Here we are presenting the first continent-wide analysis of African rainfall variability on a month-by-month and country-by-country basis. We have calculated Pearson r values for smoothed monthly rainfall data of 49 African countries over the period 1901–2017 which we compared to six potential climatic drivers of natural variability, namely AMO, NAO, ENSO (El Niño Southern Oscillation), Pacific Decadal Oscillation (PDO), Indian Ocean Dipole (IOD) and solar activity changes. We allowed time lags of up to 11 months for each potential driver (66 months for solar activity). New hydrological insights for the regionThe dynamic temporal-spatial evolution of the seasonal Pearson correlations was mapped out across the continent, tracking the gradual or abrupt expansion, displacement and subsequent waning of the various effects over the course of the year. Relationships are complicated by characteristic time lags, non-stationary correlations and occasional phase shifts. Our empirical results may help to further improve short- to midterm rainfall prognoses in Africa and provide important calibration data for the further improvement of climate models.

The Psychological Impact of COVID-19 Pandemic on the Students of Saudi Arabia

Background: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, the numbers of cases and deaths worldwide have begun to increase, the closure of schools, universities, shops, workplaces, and the vast degree of precautionary actions, have left students feeling helpless, isolated, bored, and uncertain of what would happen to their academic advancement. Our study aims to assess the degree of the psychological impact of the COVID-19 pandemic on students in Saudi Arabia. Methods: During the early days of the pandemic, the survey sample was based on non-probability sampling. We conducted an online-based survey using a snowball sample technique. The survey collected data on several aspects of the participants, including the psychological impact of COVID-19, using the Impact of Event Scale-Revised (IES-R) and the Depression, Anxiety and Stress Scale (DASS-21). The current study shows an extensive analysis of the survey with a focus on the impact of the pandemic on students. Results: A total of 336 students were recruited for the study and responded to the survey. The IES-R showed that 7.1% and 23.8% of the students experienced moderate and severe symptoms, respectively. On the DASS stress subscale, 13.4% and 10.7% of students experienced severe and extremely severe stress symptoms, respectively. With regards to anxiety, 6.0% and 15.8% of students experienced severe and extremely severe symptoms, respectively. As much as 11.6% and 17.6% of the students experienced severe and extremely severe symptoms of depression, respectively. Females were more likely to experience symptoms of Post-traumatic Stress Disorder (PTSD), stress, anxiety, and depression. Having a family member working in the field of health/medicine was significantly associated with depression; poor to average health and previous diagnosis of a psychiatric disorder was associated with a higher chance of developing PTSD, stress, anxiety, and depression. Conclusion: During the early days of the pandemic, nearly one-fourth of students experienced moderate to severe symptoms of PTSD. Our findings could help guide schools and universities in implementing a clear, effective strategy for students to navigate the coming academic year and expand the efforts made on academic and psychological counseling, especially for the vulnerable populations.

Challenging Infrastructure Project Assisted by Monitoring and Numerical Modelling as the Follo Line Tunnels were Excavated Below Existing Tunnels

Just south of Oslo Central Station, the new high-speed Follo Line railway tunnels pass beneath the existing Ekeberg road tunnels. This paper presents the construction methods, numerical model, and monitoring program used to assess the stability of the E6 road tunnels during the excavation of the Follo Line tunnels only a few metres below. The construction of the Follo Line was approved subject to three conditions: (1) there should be no negative effect on the stability of the Ekeberg tunnels, (2) the traffic flow in the Ekeberg tunnels had to be maintained at all times and (3) any risk of instability in the existing tunnels must be detected beforehand, so that necessary precautionary actions could be taken in good time. To deal with the challenges, SINTEF developed a comprehensive analysis procedure, combining continuous rock stress measurements and displacement measurements with 2D and 3D numerical modelling. The rock stress change monitoring was used together with the numerical model to monitor the stability conditions in the Ekeberg tunnels as the Follo Line tunnels were excavated. This ensured that any risk of instability in the existing tunnels could be detected in advance to enable precautionary action to be taken. The successful completion of the new tunnels without any disturbance to the road tunnels shows that the procedure would be useful for dealing with similar applications in the future.

Assessing community pharmacists' involvement and clients' opinion on HIV/AIDS services in community pharmacies in Nigeria: a cross-sectional survey.

The World Health Organization is promoting community-based services to end HIV/AIDS by 2030. In Nigeria, studies on community pharmacists' involvement in HIV testing services (HTS) and antiretroviral (ARV) medication therapy management (MTM) are scarce, and no study had evaluated the clients' opinion on community pharmacy HTS. We assessed the community pharmacists' involvement in HIV/AIDS services and clients' opinions of community pharmacy HTS. Semi-structured questionnaires on a five-point Likert scale were administered to 701 selected community pharmacists and 5840 clients in southwest Nigeria in 2019. Data were analyzed with descriptive and inferential statistics. Response rates were 68.6% and 69.8% for community pharmacists and clients, respectively. Only 18.5% of community pharmacists offered rapid HTS and 30% refills of ARV. The total score of their involvement on the HTS was 20.94 ± 17.521 (range 8-40; midpoint 24) and on ARV/MTM was 22.98 ± 19.61 (range 9-45; midpoint 27), while 91% were willing to participate in training. Barriers to integrating services into practice were lack of clinical tools (46.8%), lack of collaboration with other healthcare professionals (39.1%), and lack of training on HIV/AIDS services (36.2%) among others. Also, 77% of the clients were willing to participate in community pharmacy HTS, and about 83% of them responded that knowing their HIV status will help them to take necessary precautionary actions. Community pharmacists' involvement in HIV/AIDS services was low. However, they showed willingness to participate in training to improve services. Also, clients were willing to receive community pharmacies HTS to know their status.

The Moderating Effects of Perceived Severity on the Generational Gap in Preventive Behaviors during the COVID-19 Pandemic in the U.S.

During the COVID-19 pandemic, older adults appear to be more susceptible to the coronavirus disease. Although the health stakes are higher for older adults, individuals of all ages should adopt preventive measures to contain the human-to-human transmission of the virus. This study conducted a national online survey of 1843 adults at the early stage of the COVID-19 pandemic in the U.S. to examine age disparities in preventive behaviors against the virus. The results show that older generations, motivated by a higher perceived severity of the disease, were more likely to take the precautionary actions recommended by the U.S. Centers for Disease Control and Prevention (CDC) than younger generations. This thus suggests that persuasive health messages addressing the severity of COVID-19 might reduce the generational gap and promote preventive behaviors among young people, to protect themselves and the elderly.

Preserving SLA Parameters for Trusted IaaS Cloud: An Intelligent Monitoring Approach

Background: Cloud Computing (CC) provides an open computing feature where a large number of customers can interact with the cloud services hosted by the cloud service providers (CSP) for their business requirements. Objective: Service Level Agreements (SLAs) are legal agreements between an enterprise and the CSP. To increase the confidence of the customer towards their CSP(s) will be determined by SLA fulfillment and possible actions should be adopted to minimize the violation of the SLAs. Which in turn will also lead to the revenue generation towards CSP. When SLA is breached by the customer, penalties are imposed; whereas SLA breach by the CSP will affect the trust of its valuable customers. Methods: Identify the metrics with respect to the resources and its Service level agreements (SLAs) and measure (monitoring) this to maintain its value and if the value is less as per the SLAs (threshold values) then take precautionary actions to maintain this. Results: The results indicate the present status of the resource utilization of the CPU and categories into three levels and based upon this take necessary actions to maintain the SLAs. Conclusion: The methodology discussed herein this paper can be used for monitoring the SLA parameter and to avoid the circumstances that can lead to breaching of the SLA(s).

Airborne Microplastics from Waste as a Transmission Vector for COVID-19

Occurrences of microplastics (plastic particle < 5 mm) have been observed in various environmental media (e.g., soil, water and air) worldwide, posing a threat to ecological, human, and animal health. Microplastics could also serve as vectors which transport toxic hydrophobic organic compounds around the globe and negatively affect the environmental quality. This paper analyzes the possible link between airborne microplastics from waste that are contaminated with SARS-CoV-2, and the transmission of SARS-CoV-2. In addition, measures for controlling the transmission of SARS-CoV-2 in airborne microplastics were discussed. Our study indicates that precautionary action regarding the management of contaminated plastic waste should be considered in order to combat the spread of SARS-CoV-2 through airborne microplastic.

Modelling and predicting the spread of COVID-19 cases depending on restriction policy based on mined recommendation rules.

This paper is an extended and supplemented version of the paper "Recommendation Rules Mining for Reducing the Spread of COVID-19 Cases", presented by the authors at the 3rd International Conference on Informatics & Data-Driven Medicine in November 2020. The paper examines the impact of government restrictive measures on the spread and effects of COVID-19. The work is devoted to the improvement of recommendation rules based on novel ensemble of machine learning methods such as regression tree and clustering. The dynamics of migration between countries in clusters, and their relationship with the number of confirmed cases and the percentage of deaths caused by COVID-19, were studied on the example of Poland, Italy and Germany. It is shown that there is a clear relationship between the cluster number and the number of new cases of diseases and death. It has also been shown that different countries' policies to prevent the disease, in particular the timing of restrictive measures, correlate with the dynamics of the spread of COVID-19 and the consequences of the disease. For example, the results show a clear proactive tactic of restrictive measures by example of Germany, and catching up on the spread of the disease by example of Italy. A regression tree and guidelines about influence of features on the spreading of COVID-19 and mortality due to this infection have been constructed. The paper predicts the number of deaths due to COVID-19 on a 21-day interval using the obtained guidelines on the example of Sweden. Such forecasting was carried out for two potential government action options: with existing precautionary actions and the same precautionary actions, if they had been taken 20 days earlier (following the example of Germany). The RMSE of the mortality forecast does not exceed 4.2, which shows a good prognostic ability of the developed model. At the same time, the simulation based on the strategy of anticipatory introduction of restrictions gives 2-6% lower values of the forecast of the number of new cases. Thus, the results of this study provide an opportunity to assess the impact of decisions about restrictive measures and predict, simulate the consequences of restrictions policy.

WITHDRAWN: A new model for epidemic prediction: COVID-19 in kingdom saudi arabia case study

Coronavirus disease-2019 (COVID-19) is a viral infection that rose in a city in the Chinese province of Hubei, Wuhan. The world did not wait too long until the virus spread to reach Europe, Africa, and America to be a global pandemic. Due to the lack of information about the behaviour of the virus, several prediction models are in use all over around the world for decision making and taking precautionary actions. Therefor, in this paper, a new model named MSIR based on SIR model is proposed. The model is used to predict the spread of the disease in three cities Riyadh, Hufof and Jeddah in the kingdom of Saudi Arabia. Also the estimation of disease propagation with and without containment measure is carried out. We think that the results could be used to enhance the predictability of the pandemic outbreaks in other cities and to build long term artificial intelligence prediction model.

Responding to the pandemic at a national and state public health level

Australia’s planning and preparedness for a health emergency response has served us well in the response to the COVID-19 pandemic. Despite this, rapid and agile decisions were required to manage the public health impact. In the face of uncertainty and the seemingly evolving nature of the virus, we have seen precautionary actions and outcomes beyond that articulated in planning. The timely closure of international borders, requiring 14-day quarantine of returning travellers in designated facilities, is one such outcome; yet potentially the single most effective measure in controlling the pandemic in Australia. Our testing strategy, case and contact management, social restrictions and community measures have successfully suppressed the virus to a level of no domestic community transmission. The framework for this success was the effective utilisation of existing public health committees, whole of government leadership and responsiveness at all levels and community support. With the impending commencement of the COVID-19 vaccine program, this framework continues to support navigating our way out of the pandemic.