scholarly journals Short-term real-time prediction of total number of reported COVID-19 cases and deaths in South Africa: a data driven approach

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tarylee Reddy ◽  
Ziv Shkedy ◽  
Charl Janse van Rensburg ◽  
Henry Mwambi ◽  
Pravesh Debba ◽  
...  
Keyword(s):  
South Africa ◽  
Growth Models ◽  
National Level ◽  
Growth Curves ◽  
Gompertz Model ◽  
Logistic Growth ◽  
Short Term ◽  
Provincial Level ◽  
Maximum Period ◽  
Data Driven Approach

Abstract Background The rising burden of the ongoing COVID-19 epidemic in South Africa has motivated the application of modeling strategies to predict the COVID-19 cases and deaths. Reliable and accurate short and long-term forecasts of COVID-19 cases and deaths, both at the national and provincial level, are a key aspect of the strategy to handle the COVID-19 epidemic in the country. Methods In this paper we apply the previously validated approach of phenomenological models, fitting several non-linear growth curves (Richards, 3 and 4 parameter logistic, Weibull and Gompertz), to produce short term forecasts of COVID-19 cases and deaths at the national level as well as the provincial level. Using publicly available daily reported cumulative case and death data up until 22 June 2020, we report 5, 10, 15, 20, 25 and 30-day ahead forecasts of cumulative cases and deaths. All predictions are compared to the actual observed values in the forecasting period. Results We observed that all models for cases provided accurate and similar short-term forecasts for a period of 5 days ahead at the national level, and that the three and four parameter logistic growth models provided more accurate forecasts than that obtained from the Richards model 10 days ahead. However, beyond 10 days all models underestimated the cumulative cases. Our forecasts across the models predict an additional 23,551–26,702 cases in 5 days and an additional 47,449–57,358 cases in 10 days. While the three parameter logistic growth model provided the most accurate forecasts of cumulative deaths within the 10 day period, the Gompertz model was able to better capture the changes in cumulative deaths beyond this period. Our forecasts across the models predict an additional 145–437 COVID-19 deaths in 5 days and an additional 243–947 deaths in 10 days. Conclusions By comparing both the predictions of deaths and cases to the observed data in the forecasting period, we found that this modeling approach provides reliable and accurate forecasts for a maximum period of 10 days ahead.

scholarly journals Prediksi Akhir Pandemi COVID-19 di Indonesia dengan Simulasi Berbasis Model Pertumbuhan Parametrik

2020 ◽  
Vol 9 (2) ◽  
pp. 63-68
Author(s):  
Fransiscus Rian Pratikto
Keyword(s):  
Least Squares Method ◽  
Growth Models ◽  
Growth Curves ◽  
Nonlinear Least Squares ◽  
Gompertz Model ◽  
Population Data ◽  
Logistic Growth ◽  
Social Restriction ◽  
Nonlinear Least Squares Method

This research aims to predict the end of the COVID-19 pandemic in Indonesia based on parametric growth models. The models are chosen by considering their fitness with the data of Taiwan which is believed to have passed over the peak of the pandemic and have gone through all phases in the growth curves. The models are parameterized using the nonlinear least squares method. The deviation and confidence interval of each parameter is estimated using the k-fold cross-validation and the bootstrap techniques. Using the total cases per million population data from March 2 to June 18, 2020, it was found that two growth models fit the data, i.e. logistic and modified Gompertz, where the latter performs better. Using the information about the deviation of each model parameter, a simulation model is developed to predict the time at which the total cases curve starts to flatten, which is an indication of the end of the pandemic. It was found with 95% confidence level that based on the modified Gompertz model the pandemic will end somewhere between March 9 – September 7, 2021 with total cases per million of 206 - 555. Meanwhile, based on the logistic growth model, the end of the pandemic is between August 28 – September 23, 2020 with total cases per million of 180 - 375. This model can be extended by making comparative scenario with Taiwan based on measures that represent the quality of the pandemic mitigation such as test ratio and the intensity of social restriction.

scholarly journals The Standard Deviation Structure as a New Approach to Growth Analysis in Weight and Length Data of Farmed Lutjanus guttatus

Fishes ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 60
Author(s):  
Sergio G. Castillo-Vargasmachuca ◽  
Eugenio Alberto Aragón-Noriega ◽  
Guillermo Rodríguez-Domínguez ◽  
Leonardo Martínez-Cárdenas ◽  
Eulalio Arámbul-Muñoz ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Growth Parameters ◽  
Growth Models ◽  
Growth Curves ◽  
Gompertz Model ◽  
Information Criterion ◽  
Weight Growth ◽  
Length Data ◽  
Size At Age ◽  
The Right

In the present study, size-at-age data (length and weight) of marine cage-reared spotted rose snapper Lutjanus guttatus were analyzed under four different variance assumptions (observed, constant, depensatory, and compensatory variances) to analyze the robustness of selecting the right standard deviation structure to parametrize the von Bertalanffy, Logistic, and Gompertz models. The selection of the best model and variance criteria was obtained based on the Bayesian information criterion (BIC). According to the BIC results, the observed variance in the present study was the best way to parametrize the three abovementioned growth models, and the Gompertz model best represented the length and weight growth curves. Based on these results, using the observed error structure to calculate the growth parameters in multi-model inference analyses is recommended.

Non-Linear fitting of Sigmoidal Growth Curves to predict a maximum limit to the total number of COVID-19 cases in the United States. (Preprint)

2020 ◽  
Author(s):  
Carlos Dutra Sr
Keyword(s):  
United States ◽  
Growth Models ◽  
Growth Curves ◽  
The United States ◽  
World Health ◽  
Logistic Growth ◽  
Linear Fitting ◽  
Nonlinear Fitting ◽  
Non Linear ◽  
Maximum Limit

UNSTRUCTURED In the present work is used non-linear fitting of the "Gompert" and "Logistic" growth models to the number of total COVID-19 cases from the United States as a country and individually by states. The methodology allowed us to estimate that the maximum limit for the total number of cases of COVID-19 patients such as those registered with the World Health Organization will be approximately one million and one hundred thousand cases to the United States. Up to 04/19/20 the models indicate that United States reached 70% of this maximum number of "total cases" and the United States will reach 95% of this limit by 05/14/2020. The application of the nonlinear fitting of growth curves to the individual data of each American state showed that only 25% of them did not reach, on 04/19/20, the percentage of 59% of the maximum limit of "total cases" and that 17 of the 50 states still will not have reached 95% of that limit on 05/14/20.

scholarly journals Characterising the scale-up and performance of antiretroviral therapy programmes in sub-Saharan Africa: an observational study using growth curves

BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e034973
Author(s):  
Benjamin Bigelow ◽  
Stéphane Verguet
Keyword(s):  
Antiretroviral Therapy ◽  
Scale Up ◽  
Growth Curves ◽  
Gompertz Model ◽  
Sub Saharan Africa ◽  
Logistic Growth ◽  
Growth Curve Models ◽  
Rates Of Change ◽  
Percentage Points ◽  
Sub Saharan

ObjectivesThe rate of change in key health indicators (eg, intervention coverage) is an understudied area of health system performance. Rates of change in health services indicators can augment traditional measures that solely involve the absolute level of performance in those indicators. Growth curves are a class of mathematical models that can parameterise dynamic phenomena and estimate rates of change summarising these phenomena; however, they are not commonly used in global health. We sought to characterise the changes over time in antiretroviral therapy (ART) coverage in sub-Saharan Africa using growth curve models.DesignThis was a retrospective observational study. We used publicly available data on ART coverage levels from 2000 to 2017 in 42 sub-Saharan African countries. We developed two ordinary differential equations models, the Gompertz and logistic growth models, that allowed for the estimation of summary parameters related to scale-up and rates of change in ART coverage. We fitted non-linear regressions for the two models, assessed goodness of fit using the Bayesian information criterion (BIC), and ranked countries based on their estimated performance drawn from the fitted model parameters.ResultsWe extracted country performance in rates of scale-up of ART coverage, which ranged from ≤2.5 percentage points per year (South Sudan, Sudan, and Madagascar) to ≥8.0 percentage points per year (Benin, Zimbabwe and Namibia), using the Gompertz model. Based on BIC, the Gompertz model provided a better fit than the logistic growth model for most countries studied.ConclusionsGrowth curve models can provide benchmarks to assess country performance in ART coverage evolution. They could be a useful approach that yields summary metrics for synthesising country performance in scaling up key health services.

scholarly journals Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021

Epidemiologia ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 639-659
Author(s):  
Sushma Dahal ◽  
Ruiyan Luo ◽  
Raj Kumar Subedi ◽  
Meghnath Dhimal ◽  
Gerardo Chowell
Keyword(s):  
Performance Metrics ◽  
Growth Models ◽  
National Level ◽  
Growth Parameter ◽  
Transmission Dynamics ◽  
Short Term ◽  
Linear Pattern ◽  
Mobility Data ◽  
Using Data ◽  
Second Wave

Nepal was hard hit by a second wave of COVID-19 from April–May 2021. We investigated the transmission dynamics of COVID-19 at the national and provincial levels by using data on laboratory-confirmed RT-PCR positive cases from the official national situation reports. We performed 8 week-to-week sequential forecasts of 10-days and 20-days at national level using three dynamic phenomenological growth models from 5 March 2021–22 May 2021. We also estimated effective and instantaneous reproduction numbers at national and provincial levels using established methods and evaluated the mobility trends using Google’s mobility data. Our forecast estimates indicated a declining trend of COVID-19 cases in Nepal as of June 2021. Sub-epidemic and Richards models provided reasonable short-term projections of COVID-19 cases based on standard performance metrics. There was a linear pattern in the trajectory of COVID-19 incidence during the first wave (deceleration of growth parameter (p) = 0.41–0.43, reproduction number (Rt) at 1.1 (95% CI: 1.1, 1.2)), and a sub-exponential growth pattern in the second wave (p = 0.61 (95% CI: 0.58, 0.64)) and Rt at 1.3 (95% CI: 1.3, 1.3)). Across provinces, Rt ranged from 1.2 to 1.5 during the early growth phase of the second wave. The instantaneous Rt fluctuated around 1.0 since January 2021 indicating well sustained transmission. The peak in mobility across different areas coincided with an increasing incidence trend of COVID-19. In conclusion, we found that the sub-epidemic and Richards models yielded reasonable short-terms projections of the COVID-19 trajectory in Nepal, which are useful for healthcare utilization planning.

A MATHEMATICAL MODEL OF IMMUNE RESPONSE IN CUTANEOUS LEISHMANIASIS

2007 ◽  
Vol 15 (03) ◽  
pp. 313-354 ◽  
Author(s):  
MARCOS C. DE ALMEIDA ◽  
HELMAR N. MOREIRA
Keyword(s):  
Immune Response ◽  
Growth Models ◽  
Alternative Hypothesis ◽  
Growth Curves ◽  
Parasite Growth ◽  
Logistic Growth ◽  
Natural Immunity ◽  
Existence And Stability ◽  
Clinical Correlations ◽  
Logistic Growth Model

The TH1/TH2 paradigm has been largely used in the interpretation of several diseases, particularly in leishmaniasis. As far as we know there is no mathematical description of this model related to leishmaniasis. We have extended and modified a previous published set of equations1in order to adapt it to leishmanial disease particularities. The main modifications were: (1) the analysis of logistic and exponential parasite growth curves, (2) the assumption of the TH2 arm of the immune response having a positive action on parasite growth. The set of three simultaneous differential equations describing the TH1 arm, TH2 arm and parasite growth were analyzed for conditions of existence and stability of the solutions.Stable solutions valid for the logistic and exponential parasite growth models, with its possible clinical correlations, were obtained in the following situations: (1) parasite and TH2 extinction [TH1 cure], (2) parasite extinction and TH1/TH2 co-existence [TH1/TH2 cure], (3) TH1 and parasite co-existence, TH2 extinction [stable TH1 infection], and (4) TH1, TH2 and parasite co-existence [stable TH1/TH2 infection]. TH2 and parasite co-existence associated to TH1 extinction [stable TH2 infection] was obtained only with the logistic growth model. The model also provides an alternative hypothesis for TH1 bias in resistant mice and emphazises the importance of natural immunity for the existence of chronic states.

scholarly journals Gompertz and Logistic models for morphological traits of sudangrass cultivars during sowing seasons

2019 ◽  
Vol 40 (6Supl3) ◽  
pp. 3399
Author(s):  
Rafael Vieira Pezzini ◽  
Alberto Cargnelutti Filho ◽  
Cláudia Marques de Bem ◽  
Jéssica Maronez de Souza ◽  
Gabriela Görgen Chaves ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Plant Height ◽  
Growth Models ◽  
Logistic Models ◽  
Growth Curves ◽  
Stem Length ◽  
Logistic Growth ◽  
Thermal Sum ◽  
Independent Variable ◽  
Uniformity Trials

The use of mathematical models in the study plant growth allows the identification of phases important to the cultivars and comparison between cultivars of the same species. The objectives of this work were to fit the Gompertz and Logistic growth models for the traits of plant height and stem length as a function of the accumulated thermal sum and accumulated solar radiation, to compare the fittings and the behavior of the sudangrass cultivars and indicate the model that best describes the growth of the cultivars during four sowing seasons. Were conducted eight uniformity trials with sudangrass. At 15 days after emergence, were began the collect and evaluation of five plants from each trial. Were measured plant height and stem length. The models were fitted using the values obtained for the traits of the five plants in each evaluation as a function of the accumulated thermal sum and accumulated solar radiation. Were estimated the parameters, determined their interval of confidence, critical points in the growth curves and quality indicators of the fit. The intrinsic nonlinearities and the parameter effect were also quantified. The accumulated thermal sum and accumulated solar radiation are adequate for the use as an independent variable in the model fitted. Both models were adequate to describe the growth of the traits plant height and stem length of cultivars BRS Estribo and CG Farrapo. However, the Logistic model is more accurate.

scholarly journals Non-Linear Fitting of Sigmoidal Growth Curves to predict a maximum limit to the total number of COVID-19 cases in the United States

2020 ◽  
Author(s):  
Carlos Maximiliano Dutra
Keyword(s):  
United States ◽  
Growth Models ◽  
Growth Curves ◽  
The United States ◽  
World Health ◽  
Logistic Growth ◽  
Linear Fitting ◽  
Nonlinear Fitting ◽  
Non Linear ◽  
Maximum Limit

AbstractIn the present work is used non-linear fitting of the “Gompert” and “Logistic” growth models to the number of total COVID-19 cases from the United States as a country and individually by states. The methodology allowed us to estimate that the maximum limit for the total number of cases of COVID-19 patients such as those registered with the World Health Organization will be approximately one million and one hundred thousand cases to the United States. Up to 04/19/20 the models indicate that United States reached 70% of this maximum number of “total cases” and the United States will reach 95% of this limit by 05/14/2020. The application of the nonlinear fitting of growth curves to the individual data of each American state showed that only 25% of them did not reach, on 04/19/20, the percentage of 59% of the maximum limit of “total cases” and that 17 of the 50 states still will not have reached 95% of that limit on 05/14/20.

Good Governance

2019 ◽  
Author(s):  
Henk Addink
Keyword(s):  
South Africa ◽  
Rule Of Law ◽  
Good Governance ◽  
National Level ◽  
Administrative Law ◽  
Modern State ◽  
The Rule Of Law ◽  
The Third ◽  
Legal Perspective ◽  
Further Development

The pivotal aim of this book is to explain the creation, development, and impact of good governance from a conceptual, principal perspective and in the context of national administrative law. Three lines of reasoning have been worked out: developing the concept of good governance; specification of this concept by developing principles of good governance; and implementation of these principles of good governance on the national level. In this phase of further development of good governance, it is important to have a clear concept of good governance, presented in this book as the third cornerstone of a modern state, alongside the concepts of the rule of law and democracy. That is a rather new national administrative law perspective which is influenced by regional and international legal developments; thus, we can speak about good governance as a multilevel concept. But the question is: how is this concept of good governance further developed? Six principles of good governance (which in a narrower sense also qualify as principles of good administration) have been further specified in a systematic way, from a legal perspective. These are the principles of properness, transparency, participation, effectiveness, accountability, and human rights. Furthermore, the link has been made with integrity standards. The important developments of each of these principles are described on the national level in Europe, but also in countries outside Europe (such as Australia, Canada, and South Africa). This book gives a systematic comparison of the implementation of the principles of good governance between countries.

scholarly journals Birth prevalence of tetrahydrobiopterin deficiency in China: data from the national newborn screening program, 2013–2019

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xuelian Yuan ◽  
Jun Zhu ◽  
Hanmin Liu ◽  
Liangcheng Xiang ◽  
Yongna Yao ◽  
...  
Keyword(s):  
Screening Program ◽  
National Level ◽  
Recall Rate ◽  
Birth Prevalence ◽  
Live Births ◽  
Provincial Level ◽  
Tetrahydrobiopterin Deficiency ◽  
Total Prevalence ◽  
Entire Country ◽  
Northern Regions

Abstract Background Tetrahydrobiopterin deficiency (BH4D), a less common form of hyperphenylalaninemia (HPA), can lead to severe developmental retardation if untreated. Little has been reported on the prevalence of BH4D among live births worldwide. This study examined its prevalence across China and between geographical areas within the country. Methods We analyzed data from the Chinese national screening program for HPA in newborns between 2013 and 2019. BH4D prevalence was examined by province, region and the entire country. Provincial-level prevalence was estimated from the number of confirmed BH4D cases and screened newborns, after adjusting for HPA-positive recall rate. Regional- and national-level prevalences were estimated by summing provincial-level prevalences after weighting them by the number of live births. A Poisson distribution was assumed in order to calculate 95% confidence intervals (CIs) for prevalence. Results Among 107,078,115 newborns screened for HPA in China, 380 with BH4D were identified, corresponding to a total prevalence of 3.8 per 1,000,000 live births. Prevalence was higher in eastern regions (5.9 per 1,000,000) and northern regions (4.1 per 1,000,000) of China than in southern regions (1.6 per 1,000,000) or northwestern regions (1.7 per 1,000,000). Across the entire country, 3.9% cases of HPA were diagnosed as BH4D, and this proportion reached as high as 15.1% in the southern part of the country. Conclusions These first insights into BH4D prevalence across China suggest slightly higher prevalence than in other countries, and it varies substantially by region. More attention should be paid to early diagnosis and timely treatment of BH4D.

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