scholarly journals The heterogeneous severity of COVID-19 in African countries: A modeling approach

2021 ◽  
Author(s):  
Salihu Sabiu Musa ◽  
Xueying Wang ◽  
Shi Zhao ◽  
Shudong Li ◽  
Nafiu Hussaini ◽  
...  
Keyword(s):  
Case Fatality ◽  
Well Being ◽  
Mitigation Strategies ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Time Varying ◽  
African Countries ◽  
Awareness Campaigns ◽  
Considerable Impact ◽  
The Impact

Abstract Background: The COVID-19 pandemic has had a considerable impact on global health and economics. The impact in African countries has not been investigated through fitting epidemic models to the reported COVID-19 deaths.Method: We downloaded data for the twelve most affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying basic reproductive number (R0(t)) and infection attack rate (IAR). We developed a simple epidemic model and fitted the model to reported COVID-19 deaths in twelve African countries using iterated filtering and allowing a flexible transmission rate.Results: We observed high heterogeneity in the case-fatality rate across countries, which may be due to different reporting or testing efforts. South Africa, Tunisia, and Libya were affected most strongly, exhibiting a relatively higher(R0(t)) and infection attack rate.Conclusion: To effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvements in socioeconomic well-being, healthcare systems, the water supply, and awareness campaigns).

scholarly journals Heterogeneous Severity of COVID-19 in African Countries: A Modeling Approach

2021 ◽  
Author(s):  
Salihu Sabiu Musa ◽  
Xueying Wang ◽  
Shi Zhao ◽  
Shudong Li ◽  
Nafiu Hussaini ◽  
...  
Keyword(s):  
Epidemic Model ◽  
Attack Rate ◽  
Transmission Rate ◽  
Case Fatality ◽  
Mitigation Strategies ◽  
African Countries ◽  
Awareness Campaigns ◽  
The Impact ◽  
System Water ◽  
Tremendous Impact

Abstract Background: The COVID-19 pandemic has caused tremendous impact on global health and economics. The impact in African countries has not been investigated through fitting epidemic model to the reported COVID-19 deaths.Method: We downloaded data for the twelve most-affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying effective reproduction number (B) and infection attack rate (IAR). We developed a simple epidemic model and fitted the model to reported COVID-19 deaths in 12 African countries, using iterated filtering and allowing flexible transmission rate. Results: We found high heterogeneity in the case-fatality rate across countries, which may be due to different reporting or testing efforts. We found that South Africa, Tunisia, and Libya were hit hardest with a relatively higher a and infection attack rate Conclusion: To effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvement in socio-economic wellbeing, health care system, water supply, awareness campaigns).

scholarly journals Using outbreak data to estimate the dynamic COVID-19 landscape in Eastern Africa

2021 ◽  
Author(s):  
Mark Wamalwa ◽  
Henri E.Z. Tonnang
Keyword(s):  
Food Systems ◽  
Negative Impact ◽  
South Sudan ◽  
Eastern Africa ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Mortality Data ◽  
African Countries ◽  
Intervention Measures ◽  
The Impact

Abstract BackgroundThe emergence of Coronavirus disease 2019 (COVID-19) as a global pandemic presents a serious health threat to African countries and the livelihoods of its people. To mitigate the impact of this disease, these countries implemented intervention measures including self-isolation, the closure of schools, banning of public gatherings, social distancing and border closures. Several epidemiological models have been used to improve our understanding of COVID-19 trajectory. This has helped inform decisions about pandemic planning, resource allocation, implementation of other non-pharmaceutical interventions (NPIs). This study presents estimates of the cases and fatalities due to COVID-19 and attempts to forecast the impact of governmental interventions in Burundi, Ethiopia, Kenya, Rwanda, South Sudan, Tanzania and Uganda. .MethodsWe used time series COVID-19 case and mortality data collated from the Johns Hopkins University (JHU) repository and an extended susceptible-infected-removed (eSIR) compartmental model incorporating quarantine and vaccination compartments to account for transmission dynamics and vaccine-induced immunity over time. The predication accuracy was evaluated using the root mean square error and mean absolute error.ResultsThe number of new and confirmed cases show an exponential trend since March 02 2020. The mean basic reproductive number (R0) was between 1.32 (95% CI, 1.17 - 1.49) in Rwanda and 8.52 (95% CI: 3.73 - 14.10) in Kenya, under exponential growth. There would be a total of 115,505 (95% CI:109,999 - 121,264), 7,072,584 (6,945,505 - 7,203,084), 18,248,566(18,100,299 - 18,391,438), 410,599 (399,776 - 421528), 386,020 (376,478 - 396244), 107,265 (95,757 - 119982), 3,145,602 (3,089,070 - 3205017) infected cases under the current country blockade by January 16/2022 in Burundi, Ethiopia, Kenya, Rwanda, South Sudan, Tanzania and Uganda respectively. We show that the low apparent morbidity and mortality observed in EACs, is likely biased by underestimation of infected and mortality cases.ConclusionThe current NPI measures can effectively reduce further spread of COVID-19 and should be strengthened. The observed reduction in R0 is consistent with intervention measures implemented in EACs, in particular, lockdowns and roll-out of vaccination programmes. Future work should account for the negative impact of the interventions to the economy and food systems.

scholarly journals The impact of changes in diagnostic testing practices on estimates of COVID-19 transmission in the United States

2020 ◽  
Author(s):  
Virginia E. Pitzer ◽  
Melanie Chitwood ◽  
Joshua Havumaki ◽  
Nicolas A. Menzies ◽  
Stephanie Perniciaro ◽  
...  
Keyword(s):  
United States ◽  
Diagnostic Testing ◽  
Simulated Data ◽  
The United States ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Time Varying ◽  
Testing Practices ◽  
The Impact ◽  
Biased Estimates

AbstractEstimates of the reproductive number for novel pathogens such as SARS-CoV-2 are essential for understanding the potential trajectory of the epidemic and the level of intervention that is needed to bring the epidemic under control. However, most methods for estimating the basic reproductive number (R0) and time-varying effective reproductive number (Rt) assume that the fraction of cases detected and reported is constant through time. We explore the impact of secular changes in diagnostic testing and reporting on estimates of R0 and Rt using simulated data. We then compare these patterns to data on reported cases of COVID-19 and testing practices from different United States (US) states. We find that changes in testing practices and delays in reporting can result in biased estimates of R0 and Rt. Examination of changes in the daily number of tests conducted and the percent of patients testing positive may be helpful for identifying the potential direction of bias. Changes in diagnostic testing and reporting processes should be monitored and taken into consideration when interpreting estimates of the reproductive number of COVID-19.

scholarly journals Modelling and Analysis of 2019-nCov Epidemic in India : A study on Attack & Recovery Rate, Basic & Effective Reproductive Number, Herd Immunity Threshold & Case Fatality Ratio of Coronavirus Covid-19 in India.

2020 ◽  
Author(s):  
Tanishque Propkar Malik
Keyword(s):  
Herd Immunity ◽  
Case Fatality ◽  
Sir Model ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Case Fatality Ratio ◽  
Stochastic Sir ◽  
Novel Coronavirus ◽  
Stochastic Sir Model ◽  
The Impact

Mathematical modelling of any epidemic plays a crucial role in quantifying the impact of such pathogens. This paper focuses on building a Stochastic SIR Model with non-linear parameters (to account for the effect of lockdowns) to gain a broader cognition of the 2019 novel Coronavirus pathogen (2019-nCov), widely known as Covid-19, in India. Such models help in gauging the virulence and fecundity of pathogens. Based on early transmission dynamics the basic reproductive number (R0) is computed to be 1.605. Whereas, effective reproductive number (Rt) is computed to be 4.880 as on 19 March, 2.756 as on 19 April, and 1.995 as on 19 May. Furthermore, the proportion of population that needs to be immunized (through inoculation, recovery, or death) to halt the infection spread is estimated to be 37.69%, ergo, the Herd Immunity Threshold is estimated to be 51.36 crores recoveries, if the Rt remains below 2. Rt is expected to fall below 2, and the Case Fatality Ratio (CFR) to fall to 2.14%, circa early-September (assuming minimal or no medical breakthroughs). The formulated model also provides inferential evidence manifesting the extent to which lockdowns contained the spread of the virus.

scholarly journals Impact of Globalisation on African and Its Implications to Education

2020 ◽  
Vol 1 (1) ◽  
pp. p81
Author(s):  
Titus Ogalo Pacho
Keyword(s):  
Well Being ◽  
African Countries ◽  
Cultural Economic ◽  
Global Society ◽  
The World ◽  
Theoretical Paper ◽  
Environmental Events ◽  
Almost All ◽  
The Impact ◽  
Diverse Cultures

Globalisation is one of the most powerful worldwide forces transforming society. It dominates today’s world as a major driver of change. Globalisation has brought about an agglomeration of cultures, where diverse cultures not only interact but also sometimes clash. It permeates through all spheres of life including the environment, politics, economy, prosperity, culture, religion, education, and human well-being in societies across the globe. The present “villagization” of the world has greatly affected many African countries in almost all aspects of life. It has done so in both positive and negative ways. With the emergence of a global society, social, cultural, economic, political, technological and environmental events in one part of the world quickly come to be significant for people in other parts of the world. This theoretical paper assesses the impact of globalisation for Africa and its implications to education.

SE2IR Invest Market Rumor Spreading Model Considering Hesitating Mechanism

2019 ◽  
Vol 7 (1) ◽  
pp. 54-69 ◽  
Author(s):  
Hongxing Yao ◽  
Xiangyang Gao
Keyword(s):  
Mean Field ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Field Equations ◽  
Rumor Spreading ◽  
Immunization Strategy ◽  
Scale Free ◽  
Spreading Model ◽  
Mean Field Equations ◽  
The Impact

Abstract According to the actual situation of investor network, a SE2IR rumor spreading model with hesitating mechanism is proposed, and the corresponding mean-field equations is obtained on scale-free network. In this paper, we first combine the theory of spreading dynamics and find out the basic reproductive number R0. And then analyzes the stability of the rumor-free equilibrium and the final rumor size. Finally, we discuss random immune strategies and target immune strategies for the rumor spreading, respectively. Through numerical simulation, we can draw the following conclusions: Reducing the fuzziness and attractiveness of invest market rumor can effectively reduce the impact of rumor. And the target immunization strategy is more effective than the random immunization strategy for the communicators in the invest investor network.

HEPATITIS C VIRUS AND INTRAVENOUS DRUG MISUSE: A MODELING APPROACH

2014 ◽  
Vol 07 (01) ◽  
pp. 1450006 ◽  
Author(s):  
STEADY MUSHAYABASA ◽  
CLAVER P. BHUNU
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Steady States ◽  
Transmission Dynamics ◽  
Intravenous Drug ◽  
Basic Reproductive Number ◽  
Drug Misuse ◽  
Dynamical Analysis ◽  
Reproductive Number ◽  
The Impact

Hepatitis C virus (HCV) is a blood-borne infection that can lead to progressive liver failure, cirrhosis, hepatocellular carcinoma and death. A deterministic mathematical model for assessing the impact of daily intravenous drug misuse on the transmission dynamics of HCV is presented and analyzed. A threshold quantity known as the reproductive number has been computed. Stability of the steady states has been investigated. The dynamical analysis reveals that the model has globally asymptotically stable steady states. The impact of daily intravenous drug misuse on the transmission dynamics of HCV has been discussed through the basic reproductive number and numerical simulations.

scholarly journals A Simulation on Potential Secondary Spread of Novel Coronavirus in an Exported Country Using a Stochastic Epidemic SEIR Model

2020 ◽  
Vol 9 (4) ◽  
pp. 944 ◽  
Author(s):  
Kentaro Iwata ◽  
Chisato Miyakoshi
Keyword(s):  
Healthcare Professionals ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Asian Countries ◽  
Hospital Visit ◽  
Seir Model ◽  
Stochastic Epidemic ◽  
Novel Coronavirus ◽  
The Impact ◽  
Multiple Scenarios

Ongoing outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of new patients continues to increase. Even though it began to spread to many other parts of the world, such as other Asian countries, the Americas, Europe, and the Middle East, the impact of secondary outbreaks caused by exported cases outside China remains unclear. We conducted simulations to estimate the impact of potential secondary outbreaks in a community outside China. Simulations using stochastic SEIR model were conducted, assuming one patient was imported to a community. Among 45 possible scenarios we prepared, the worst scenario resulted in the total number of persons recovered or removed to be 997 (95% CrI 990–1000) at day 100 and a maximum number of symptomatic infectious patients per day of 335 (95% CrI 232–478). Calculated mean basic reproductive number (R0) was 6.5 (Interquartile range, IQR 5.6–7.2). However, better case scenarios with different parameters led to no secondary cases. Altering parameters, especially time to hospital visit. could change the impact of a secondary outbreak. With these multiple scenarios with different parameters, healthcare professionals might be able to better prepare for this viral infection.

scholarly journals Modeling influenza seasonality in the tropics and subtropics

2021 ◽  
Vol 17 (6) ◽  
pp. e1009050
Author(s):  
Haokun Yuan ◽  
Sarah C. Kramer ◽  
Eric H. Y. Lau ◽  
Benjamin J. Cowling ◽  
Wan Yang
Keyword(s):  
Hong Kong ◽  
Mechanistic Model ◽  
Seasonal Pattern ◽  
Influenza Viruses ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Influenza Surveillance ◽  
Influenza Epidemic ◽  
Influenza Transmission ◽  
The Impact

Climate drivers such as humidity and temperature may play a key role in influenza seasonal transmission dynamics. Such a relationship has been well defined for temperate regions. However, to date no models capable of capturing the diverse seasonal pattern in tropical and subtropical climates exist. In addition, multiple influenza viruses could cocirculate and shape epidemic dynamics. Here we construct seven mechanistic epidemic models to test the effect of two major climate drivers (humidity and temperature) and multi-strain co-circulation on influenza transmission in Hong Kong, an influenza epidemic center located in the subtropics. Based on model fit to long-term influenza surveillance data from 1998 to 2018, we found that a simple model incorporating the effect of both humidity and temperature best recreated the influenza epidemic patterns observed in Hong Kong. The model quantifies a bimodal effect of absolute humidity on influenza transmission where both low and very high humidity levels facilitate transmission quadratically; the model also quantifies the monotonic but nonlinear relationship with temperature. In addition, model results suggest that, at the population level, a shorter immunity period can approximate the co-circulation of influenza virus (sub)types. The basic reproductive number R0 estimated by the best-fit model is also consistent with laboratory influenza survival and transmission studies under various combinations of humidity and temperature levels. Overall, our study has developed a simple mechanistic model capable of quantifying the impact of climate drivers on influenza transmission in (sub)tropical regions. This model can be applied to improve influenza forecasting in the (sub)tropics in the future.

scholarly journals Transmission dynamics of SARS-COV-2 in China: impact of public health interventions

2020 ◽  
Author(s):  
Wenbao Wang ◽  
Yiqin Chen ◽  
Qi Wang ◽  
Ping Cai ◽  
Ye He ◽  
...  
Keyword(s):  
Public Health ◽  
Health Interventions ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Public Health Interventions ◽  
The Public ◽  
Global Pandemic ◽  
Actual Growth ◽  
Global Threat ◽  
The Impact

AbstractCOVID-19 has become a global pandemic. However, the impact of the public health interventions in China needs to be evaluated. We established a SEIRD model to simulate the transmission trend of China. In addition, the reduction of the reproductive number was estimated under the current forty public health interventions policies. Furthermore, the infection curve, daily transmission replication curve, and the trend of cumulative confirmed cases were used to evaluate the effects of the public health interventions. Our results showed that the SEIRD curve model we established had a good fit and the basic reproductive number is 3.38 (95% CI, 3.25–3.48). The SEIRD curve show a small difference between the simulated number of cases and the actual number; the correlation index (H2) is 0.934, and the reproductive number (R) has been reduced from 3.38 to 0.5 under the current forty public health interventions policies of China. The actual growth curve of new cases, the virus infection curve, and the daily transmission replication curve were significantly going down under the current public health interventions. Our results suggest that the current public health interventions of China are effective and should be maintained until COVID-19 is no longer considered a global threat.

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