scholarly journals Accessing the Syndemic of COVID-19 and Malaria Intervention in Africa

2020 ◽  
Author(s):  
Benyun Shi ◽  
Jinxin Zheng ◽  
Shang Xia ◽  
Shan Lin ◽  
Xinyi Wang ◽  
...  
Keyword(s):  
Malaria Transmission ◽  
Sub Saharan Africa ◽  
Cumulative Number ◽  
Insecticide Treated Nets ◽  
Middle Income ◽  
Social Distancing ◽  
Transmission Potential ◽  
Epidemic Dynamics ◽  
The Impact ◽  
Epidemiological Parameters

Abstract Background: The COVID-19 pandemic has caused substantial disruptions to health services in the low and middle-income countries with a high burden of other diseases, such as malaria in sub-Saharan Africa. As the COVID-19 pandemic spread to Africa, there is an urgent need to assess the impact of COVID-19 pandemic on malaria transmission potential in malaria-endemic countries in Africa.Methods: We present a data-driven method to quantify the extent to which the COVID-19 pandemic, as well as various non-pharmaceutical interventions (NPIs), could lead to the change of malaria transmission potential in 2020. First, we adopt a particle Markov Chain Monte Carlo method to estimate epidemiological parameters in each country by fitting the time series of the cumulative number of COVID-19 cases. Then, we simulate the epidemic dynamics of COVID-19 under two groups of NPIs: (i) contact restriction and social distancing, and (ii) early identification and isolation of cases. Based on the simulated epidemic curves, we quantify the impact of COVID-19 epidemic and NPIs on the distribution of insecticide-treated nets (ITNs). Finally, by treating the total number of ITNs available in each country in 2020, we evaluate the negative effects of COVID-19 pandemic on malaria transmission potential based on the notion of vectorial capacity.Results: We conduct case studies in four malaria-endemic countries, Ethiopia, Nigeria, Tanzania, and Zambia, in Africa. The epidemiological parameters (i.e., the basic reproduction number R0 and the duration of infection DI ) of COVID-19 in each country are estimated as follows: Ethiopia (R0 = 1:57, DI = 5:32), Nigeria (R0 = 2:18, DI = 6:58), Tanzania (R0 = 2:47, DI = 6:01), and Zambia (R0 = 2:12, DI = 6:96). Based on the estimated epidemiological parameters, the epidemic curves simulated under various NPIs indicated that the earlier the interventions are implemented, the better the epidemic is controlled. Moreover, the effect of combined NPIs is better than contact restriction and social distancing only. By treating the total number of ITNs available in each country in 2020 as a baseline, our results show that even with stringent NPIs, malaria transmission potential will remain higher than expected in the second half of 2020.Conclusions: By quantifying the impact of various NPI response to the COVID-19 pandemic on malaria transmission potential, this study provides a way to jointly address the syndemic between COVID-19 and malaria in malaria-endemic countries in Africa. The results suggest that the early intervention of COVID-19 can effectively reduce the scale of the epidemic and mitigate its impact on malaria transmission potential.

scholarly journals Accessing the syndemic of COVID-19 and malaria intervention in Africa

2020 ◽  
Author(s):  
Benyun Shi ◽  
Jinxin Zheng ◽  
Shang Xia ◽  
Shan Lin ◽  
Xinyi Wang ◽  
...  
Keyword(s):  
Malaria Transmission ◽  
Sub Saharan Africa ◽  
Cumulative Number ◽  
Insecticide Treated Nets ◽  
Middle Income ◽  
Social Distancing ◽  
Transmission Potential ◽  
Epidemic Dynamics ◽  
The Impact ◽  
Epidemiological Parameters

Abstract Background: The COVID-19 pandemic has caused substantial disruptions to health services in the low and middle-income countries with a high burden of other diseases, such as malaria in sub-Saharan Africa. As the COVID-19 pandemic spread to Africa, there is an urgent need to assess the impact of COVID-19 pandemic on malaria transmission potential in malaria-endemic countries in Africa. Methods: We present a data-driven method to quantify the extent to which the COVID-19 pandemic, as well as various non-pharmaceutical interventions (NPIs), could lead to the change of malaria transmission potential in 2020. First, we adopt a particle Markov Chain Monte Carlo method to estimate epidemiological parameters in each country by fitting the time series of the cumulative number of reported COVID-19 cases. Then, we simulate the epidemic dynamics of COVID-19 under two groups of NPIs: (i) contact restriction and social distancing, and (ii) early identification and isolation of cases. Based on the simulated epidemic curves, we quantify the impact of COVID-19 epidemic and NPIs on the distribution of insecticide-treated nets (ITNs). Finally, by treating the total number of ITNs available in each country in 2020, we evaluate the negative effects of COVID-19 pandemic on malaria transmission potential based on the notion of vectorial capacity. Results: In this paper, we conduct case studies in four malaria-endemic countries, Ethiopia, Nigeria, Tanzania, and Zambia, in Africa. The epidemiological parameters (i.e., the basic reproduction number R_0 and the duration of infection DI) of COVID-19 in each country are estimated as follows: Ethiopia (R0=1.57, DI=5.32), Nigeria (R0=2.18, DI=6.58), Tanzania (R0=2.47, DI=6.01), and Zambia (R0=2.12, DI=6.96). Based on the estimated epidemiological parameters, the epidemic curves simulated under various NPIs indicated that the earlier the interventions are implemented, the better the epidemic is controlled. Moreover, the effect of combined NPIs is better than contact restriction and social distancing only. By treating the total number of ITNs available in each country in 2020 as a baseline, our results show that even with stringent NPIs, malaria transmission potential will remain higher than expected in the second half of 2020. Conclusions: By quantifying the impact of various NPI response to the COVID-19 pandemic on malaria transmission potential, this study provides a way to jointly address the syndemic between COVID-19 and malaria in malaria-endemic countries in Africa. The results suggest that the early intervention of COVID-19 can effectively reduce the scale of the epidemic and mitigate its impact on malaria transmission potential.

scholarly journals Accessing the syndemic of COVID-19 and malaria intervention in Africa

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Benyun Shi ◽  
Jinxin Zheng ◽  
Shang Xia ◽  
Shan Lin ◽  
Xinyi Wang ◽  
...  
Keyword(s):  
Malaria Transmission ◽  
Sub Saharan Africa ◽  
Cumulative Number ◽  
Insecticide Treated Nets ◽  
Middle Income ◽  
Social Distancing ◽  
Transmission Potential ◽  
Epidemic Dynamics ◽  
The Impact ◽  
Epidemiological Parameters

Abstract Background The pandemic of the coronavirus disease 2019 (COVID-19) has caused substantial disruptions to health services in the low and middle-income countries with a high burden of other diseases, such as malaria in sub-Saharan Africa. The aim of this study is to assess the impact of COVID-19 pandemic on malaria transmission potential in malaria-endemic countries in Africa. Methods We present a data-driven method to quantify the extent to which the COVID-19 pandemic, as well as various non-pharmaceutical interventions (NPIs), could lead to the change of malaria transmission potential in 2020. First, we adopt a particle Markov Chain Monte Carlo method to estimate epidemiological parameters in each country by fitting the time series of the cumulative number of reported COVID-19 cases. Then, we simulate the epidemic dynamics of COVID-19 under two groups of NPIs: (1) contact restriction and social distancing, and (2) early identification and isolation of cases. Based on the simulated epidemic curves, we quantify the impact of COVID-19 epidemic and NPIs on the distribution of insecticide-treated nets (ITNs). Finally, by treating the total number of ITNs available in each country in 2020, we evaluate the negative effects of COVID-19 pandemic on malaria transmission potential based on the notion of vectorial capacity. Results We conduct case studies in four malaria-endemic countries, Ethiopia, Nigeria, Tanzania, and Zambia, in Africa. The epidemiological parameters (i.e., the basic reproduction number $$R_0$$ R 0 and the duration of infection $$D_I$$ D I ) of COVID-19 in each country are estimated as follows: Ethiopia ($$R_0=1.57$$ R 0 = 1.57 , $$D_I=5.32$$ D I = 5.32 ), Nigeria ($$R_0=2.18$$ R 0 = 2.18 , $$D_I=6.58$$ D I = 6.58 ), Tanzania ($$R_0=2.47$$ R 0 = 2.47 , $$D_I=6.01$$ D I = 6.01 ), and Zambia ($$R_0=2.12$$ R 0 = 2.12 , $$D_I=6.96$$ D I = 6.96 ). Based on the estimated epidemiological parameters, the epidemic curves simulated under various NPIs indicated that the earlier the interventions are implemented, the better the epidemic is controlled. Moreover, the effect of combined NPIs is better than contact restriction and social distancing only. By treating the total number of ITNs available in each country in 2020 as a baseline, our results show that even with stringent NPIs, malaria transmission potential will remain higher than expected in the second half of 2020. Conclusions By quantifying the impact of various NPI response to the COVID-19 pandemic on malaria transmission potential, this study provides a way to jointly address the syndemic between COVID-19 and malaria in malaria-endemic countries in Africa. The results suggest that the early intervention of COVID-19 can effectively reduce the scale of the epidemic and mitigate its impact on malaria transmission potential.

scholarly journals Accessing the syndemic of COVID-19 and malaria intervention in Africa

2020 ◽  
Author(s):  
Benyun Shi ◽  
Jinxin Zheng ◽  
Shang Xia ◽  
Shan Lin ◽  
Xinyi Wang ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Malaria Transmission ◽  
Vectorial Capacity ◽  
Insecticide Treated Nets ◽  
Transmission Potential ◽  
The Impact ◽  
Pharmaceutical Interventions ◽  
Epidemiological Parameters

Abstract Background: The pandemic of the coronavirus disease 2019 (COVID-19) has caused substantial disruptions to health services in the low and middle-income countries with a high burden of other diseases, such as malaria in sub-Saharan Africa. The aim of this study is to assess the impact of COVID-19 pandemic on malaria transmission potential in malaria-endemic countries in Africa. Methods: We present a data-driven method to quantify the extent to which the COVID-19 pandemic, as well as various non-pharmaceutical interventions (NPIs), could lead to the change of malaria transmission potential in 2020. First, we adopt a particle Markov Chain Monte Carlo method to estimate epidemiological parameters in each country by fitting the time series of the cumulative number of reported COVID-19 cases. Then, we simulate the epidemic dynamics of COVID-19 under two groups of NPIs: (i) contact restriction and social distancing, and (ii) early identification and isolation of cases. Based on the simulated epidemic curves, we quantify the impact of COVID-19 epidemic and NPIs on the distribution of insecticide-treated nets (ITNs). Finally, by treating the total number of ITNs available in each country in 2020, we evaluate the negative effects of COVID-19 pandemic on malaria transmission potential based on the notion of vectorial capacity. Results: In this paper, we conduct case studies in four malaria-endemic countries, Ethiopia, Nigeria, Tanzania, and Zambia, in Africa. The epidemiological parameters (i.e., the basic reproduction number R_0 and the duration of infection D_I) of COVID-19 in each country are estimated as follows: Ethiopia (R_0=1.57, D_I=5.32), Nigeria (R_0=2.18, D_I=6.58), Tanzania (R_0=2.47, D_I=6.01), and Zambia (R_0=2.12, D_I=6.96). Based on the estimated epidemiological parameters, the epidemic curves simulated under various NPIs indicated that the earlier the interventions are implemented, the better the epidemic is controlled. Moreover, the effect of combined NPIs is better than contact restriction and social distancing only. By treating the total number of ITNs available in each country in 2020 as a baseline, our results show that even with stringent NPIs, malaria transmission potential will remain higher than expected in the second half of 2020. Conclusions: By quantifying the impact of various NPI response to the COVID-19 pandemic on malaria transmission potential, this study provides a way to jointly address the syndemic between COVID-19 and malaria in malaria-endemic countries in Africa. The results suggest that the early intervention of COVID-19 can effectively reduce the scale of the epidemic and mitigate its impact on malaria transmission potential. Keywords : COVID-19 pandemic; Non-pharmaceutical interventions; Particle Markov chain Monte Carlo; Insecticide-treated nets; Vectorial capacity; Malaria transmission potential

scholarly journals Risk of Plasmodium falciparum infection in south-west Burkina Faso - potential impact of expanding eligibility for seasonal malaria chemoprevention

2021 ◽  
Author(s):  
Anne L Wilson ◽  
Steve W Lindsay ◽  
Alfred Tiono ◽  
Jean Baptiste Yaro ◽  
Hilary Ranson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Plasmodium Falciparum ◽  
Burkina Faso ◽  
Malaria Transmission ◽  
Malaria Control ◽  
Control Measures ◽  
Sub Saharan Africa ◽  
South West ◽  
Seasonal Malaria Chemoprevention ◽  
The Impact

Abstract Background Burkina Faso has one of the highest malaria burdens in sub-Saharan Africa despite the mass deployment of insecticide-treated nets (ITNs) and use of seasonal malaria chemoprevention (SMC) in children aged up to 5 years. Identification of risk factors for Plasmodium falciparum infection in rural Burkina Faso could help to identify and target malaria control measures. Methods A cross-sectional survey of 1,199 children and adults was conducted during the peak malaria transmission season in south-west Burkina Faso in 2017. Logistic regression was used to identify risk factors for microscopically confirmed P. falciparum infection. A malaria transmission dynamic model was used to determine the impact on malaria cases averted of administering SMC to children aged 5–15 year old. Results P. falciparum prevalence was 32.8% in the study population. Children aged 5 to < 10 years old were at 3.74 times the odds (95% CI = 2.68–5.22, p < 0.001) and children aged 10 to 15 years old at 3.14 times the odds (95% CI = 1.20–8.21, p = 0.02) of P. falciparum infection compared to children aged less than 5 years old. Administration of SMC to children aged up to 10 years is predicted to avert an additional 57 malaria cases per 1000 population per year (9.4% reduction) and administration to children aged up to 15 years would avert an additional 89 malaria cases per 1000 population per year (14.6% reduction) in the Cascades Region, assuming coverage of pyrethroid-piperonyl butoxide ITNs. Conclusion Malaria infections were high in all age strata, although highest in children aged 5 to 15 years, despite roll out of core malaria control interventions. Given the burden of infection in school-age children, extension of the eligibility criteria for SMC could help reduce the burden of malaria in Burkina Faso and other countries in the region.

scholarly journals Impact of Feed the Future initiative on nutrition in children aged less than 5 years in sub-Saharan Africa: difference-in-differences analysis

BMJ ◽  
2019 ◽  
pp. l6540 ◽  
Author(s):  
Theresa Ryckman ◽  
Margaret Robinson ◽  
Courtney Pedersen ◽  
Jay Bhattacharya ◽  
Eran Bendavid
Keyword(s):  
Sub Saharan Africa ◽  
Difference In Differences ◽  
Large Country ◽  
Middle Income ◽  
National Differences ◽  
Low Weight ◽  
The Future ◽  
Sub Saharan ◽  
Feed The Future ◽  
The Impact

AbstractObjectiveTo evaluate the impact of the US government’s Feed the Future initiative on nutrition outcomes in children younger than 5 years in sub-Saharan Africa.DesignDifference-in-differences quasi-experimental approach.SettingHouseholds in 33 low and lower middle income countries in sub-Saharan Africa.Population883 309 children aged less than 5 years with weight, height, and age recorded in 118 surveys conducted in 33 countries between 2000 and 2017: 388 052 children were from Feed the Future countries and 495 257 were from non-Feed the Future countries.Main outcome measuresA difference-in-differences approach was used to compare outcomes among children in intervention countries after implementation of the initiative with children before its introduction and children in non-intervention countries, controlling for relevant covariates, time invariant national differences, and time trends. The primary outcome was stunting (height for age >2 standard deviations below a reference median), a key indicator of undernutrition in children. Secondary outcomes were wasting (low weight for height) and underweight (low weight for age).ResultsAcross all years and countries, 38.3% of children in the study sample were stunted, 8.9% showed wasting, and 21.3% were underweight. In the first six years of Feed the Future’s implementation, children in 12 countries with the initiative exhibited a 3.9 percentage point (95% confidence interval 2.4 to 5.5) greater decline in stunting, a 1.1 percentage point (0.1 to 2.1) greater decline in wasting, and a 2.8 percentage point (1.6 to 4.0) greater decline in underweight levels compared with children in 21 countries without the initiative and compared with trends in undernutrition before Feed the Future was launched. These decreases translate to around two million fewer stunted and underweight children aged less than 5 years and around a half million fewer children with wasting. For context, about 22 million children were stunted, 11 million children were underweight, and four million children were wasted in the Feed the Future countries at baseline.ConclusionsFeed the Future’s activities were closely linked to notable improvements in stunting and underweight levels and moderate improvements in wasting in children younger than 5 years. These findings highlight the effectiveness of this large, country tailored initiative focused on agriculture and food security and have important implications for the future of this and other nutrition interventions worldwide.

scholarly journals Early estimates of COVID-19 infections in small, medium and large population clusters

2020 ◽  
Vol 5 (9) ◽  
pp. e003055
Author(s):  
Amir Siraj ◽  
Alemayehu Worku ◽  
Kiros Berhane ◽  
Maru Aregawi ◽  
Munir Eshetu ◽  
...  
Keyword(s):  
Large Population ◽  
Face Mask ◽  
Sub Saharan Africa ◽  
Contact Tracing ◽  
Local Context ◽  
African Region ◽  
Social Distancing ◽  
Population Sizes ◽  
Sub Saharan ◽  
The Impact

IntroductionSince its emergence in late December 2019, COVID-19 has rapidly developed into a pandemic in mid of March with many countries suffering heavy human loss and declaring emergency conditions to contain its spread. The impact of the disease, while it has been relatively low in the sub-Saharan Africa (SSA) as of May 2020, is feared to be potentially devastating given the less developed and fragmented healthcare system in the continent. In addition, most emergency measures practised may not be effective due to their limited affordability as well as the communal way people in SSA live in relative isolation in clusters of large as well as smaller population centres.MethodsTo address the acute need for estimates of the potential impacts of the disease once it sweeps through the African region, we developed a process-based model with key parameters obtained from recent studies, taking local context into consideration. We further used the model to estimate the number of infections within a year of sustained local transmissions under scenarios that cover different population sizes, urban status, effectiveness and coverage of social distancing, contact tracing and usage of cloth face mask.ResultsWe showed that when implemented early, 50% coverage of contact tracing and face mask, with 33% effective social distancing policies can bringing the epidemic to a manageable level for all population sizes and settings we assessed. Relaxing of social distancing in urban settings from 33% to 25% could be matched by introduction and maintenance of face mask use at 43%.ConclusionsIn SSA countries with limited healthcare workforce, hospital resources and intensive care units, a robust system of social distancing, contact tracing and face mask use could yield in outcomes that prevent several millions of infections and thousands of deaths across the continent.

scholarly journals Modelling the Potential Impact of Social Distancing on the COVID-19 Epidemic in South Africa

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
F. Nyabadza ◽  
F. Chirove ◽  
C. W. Chukwu ◽  
M. V. Visaya
Keyword(s):  
South Africa ◽  
Deterministic Model ◽  
Cumulative Number ◽  
The Novel ◽  
Social Distancing ◽  
The Social ◽  
Potential Impact ◽  
Policy Direction ◽  
Novel Coronavirus ◽  
The Impact

The novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. With the global spread increasing and infecting millions, containment efforts by countries have largely focused on lockdowns and social distancing to minimise contact between persons. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to describe the impact of social distancing on the transmission dynamics of COVID-19 in South Africa. The model is fitted to data from March 5 to April 13, 2020, on the cumulative number of infected cases, and a scenario analysis on different levels of social distancing is presented. The model shows that with the levels of social distancing under the initial lockdown level between March 26 and April 13, 2020, there would be a projected continued rise in the number of infected cases. The model also looks at the impact of relaxing the social distancing measures after the initial announcement of the lockdown. It is shown that relaxation of social distancing by 2% can result in a 23% rise in the number of cumulative cases whilst an increase in the level of social distancing by 2% would reduce the number of cumulative cases by about 18%. The model results accurately predicted the number of cases after the initial lockdown level was relaxed towards the end of April 2020. These results have implications on the management and policy direction in the early phase of the epidemic.

scholarly journals Epidemiological Modeling of COVID-19 in Saudi Arabia: Spread Projection, Awareness, and Impact of Treatment

2020 ◽  
Vol 10 (17) ◽  
pp. 5895 ◽  
Author(s):  
Yousef Alharbi ◽  
Abdulrahman Alqahtani ◽  
Olayan Albalawi ◽  
Mohsen Bakouri
Keyword(s):  
Saudi Arabia ◽  
Information Criterion ◽  
Sir Model ◽  
Cumulative Number ◽  
Epidemiological Modeling ◽  
Social Distancing ◽  
Epidemic Size ◽  
Statistical Indices ◽  
First Case ◽  
The Impact

The first case of COVID-19 originated in Wuhan, China, after which it spread across more than 200 countries. By 21 July 2020, the rapid global spread of this disease had led to more than 15 million cases of infection, with a mortality rate of more than 4.0% of the total number of confirmed cases. This study aimed to predict the prevalence of COVID-19 and to investigate the effect of awareness and the impact of treatment in Saudi Arabia. In this paper, COVID-19 data were sourced from the Saudi Ministry of Health, covering the period from 31 March 2020 to 21 July 2020. The spread of COVID-19 was predicted using four different epidemiological models, namely the susceptible–infectious–recovered (SIR), generalized logistic, Richards, and Gompertz models. The assessment of models’ fit was performed and compared using four statistical indices (root-mean-square error (RMSE), R squared (R2), adjusted R2 ( Radj2), and Akaike’s information criterion (AIC)) in order to select the most appropriate model. Modified versions of the SIR model were utilized to assess the influence of awareness and treatment on the prevalence of COVID-19. Based on the statistical indices, the SIR model showed a good fit to reported data compared with the other models (RMSE = 2790.69, R2 = 99.88%, Radj2 = 99.98%, and AIC = 1796.05). The SIR model predicted that the cumulative number of infected cases would reach 359,794 and that the pandemic would end by early September 2020. Additionally, the modified version of the SIR model with social distancing revealed that there would be a reduction in the final cumulative epidemic size by 9.1% and 168.2% if social distancing were applied over the short and long term, respectively. Furthermore, different treatment scenarios were simulated, starting on 8 July 2020, using another modified version of the SIR model. Epidemiological modeling can help to predict the cumulative number of cases of infection and to understand the impact of social distancing and pharmaceutical intervention on the prevalence of COVID-19. The findings from this study can provide valuable information for governmental policymakers trying to control the spread of this pandemic.

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