scholarly journals Mathematical Modeling and Covid-19 Forecast in Texas, USA: a prediction model analysis and the probability of disease outbreak

2021 ◽  
pp. 1-27
Author(s):  
Md Nazmul Hassan ◽  
Md. Shahriar Mahmud ◽  
Kaniz Fatema Nipa ◽  
Md. Kamrujjaman
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Current Trend ◽  
Effective Vaccine ◽  
Third Wave ◽  
Continuous Time Markov Chain ◽  
State Health ◽  
Department Of State ◽  
Texas Department ◽  
Future Prediction

Abstract Background Response to the unprecedented COVID-19 outbreak needs to be augmented in Texas, USA, where the first 5 cases were reported on March 6, 2020, were rapidly followed by an exponential rise within the next few weeks. This study aimed to determine the ongoing trend and upcoming infection status of COVID-19 in county levels of Texas. Methods Data were extracted from the following sources: published literature, surveillance, unpublished reports, and websites of Texas Department of State Health Services (DSHS), Natality report of Texas and WHO Coronavirus Disease (COVID-19) Dashboard. Four-compartment Susceptible-Exposed-Infectious-Removal (SEIR) mathematical model was used to estimate the current trend and future prediction of basic reproduction number and infection case in Texas. Since the basic reproduction number is not sufficient to predict the outbreak, we applied the Continuous-Time Markov Chain (CTMC) model to calculate the probability of the COVID-19 outbreak. Results The estimated mean basic reproduction number of COVID-19 in Texas is predicted 2.65 by January 31, 2021. Our model indicated that the third wave might occur at the beginning of May of 2021, which will peak at the end of June 2021. This prediction may come true if the current spreading situation/level persists, i.e., no clinically effective vaccine is available,or this vaccination program fails for some reason in this area. Conclusion Our analysis indicates an alarming ongoing and upcoming infection rate of COVID-19 at county levels of Texas, thereby emphasizing promoting more coordinated and disciplined actions by both policymakers and the population to contain its devastating impact.

Epidemiology Surveillance and Capacity Improvement: A Characterization of Texas, 2017

2021 ◽  
pp. 1-8
Author(s):  
Kahler W. Stone ◽  
Marilyn Felkner ◽  
Eric Garza ◽  
Maria Perez-Patron ◽  
Cason Schmit ◽  
...  
Keyword(s):  
Public Health ◽  
Health Department ◽  
Local Health ◽  
State Health ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
State Health Department ◽  
Department Of State ◽  
Texas Department ◽  
Funding Programs

Abstract Objectives: In response to increasing caseloads of foodborne illnesses and high consequence infectious disease investigations, the Texas Department of State Health Services (DSHS) requested funding from the Texas Legislature in 2013 and 2015 for a new state-funded epidemiologist (SFE) program. Methods: Primary cross-sectional survey data were collected from 32 of 40 local health departments (LHDs) via an online instrument and analyzed to quantify roles, responsibilities, and training of epidemiologists in Texas in 2017 and compared to similar state health department assessments. Results: Sixty-six percent of SFEs had epidemiology-specific training (eg, master’s in public health) compared to 45% in state health department estimates. For LHDs included in this study, the mean number of epidemiologists per 100 000 was 0.73 in medium LHDs and 0.46 in large LHDs. SFE positions make up approximately 40% of the LHD epidemiology workforce of all sizes and 56% of medium-sized LHD epidemiology staff in Texas specifically. Conclusions: Through this program, DSHS increased epidemiology capacity almost twofold from 0.28 to 0.47 epidemiologists per 100 000 people. These findings suggest that capacity funding programs like this improve epidemiology capacity in local jurisdictions and should be considered in other regions to improve general public health preparedness and epidemiology capacity.

scholarly journals A Data Driven Analysis and Forecast of COVID-19 Dynamics during the Third Wave Using SIRD Model in Bangladesh

COVID ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 503-517
Author(s):  
Omar Faruk ◽  
Suman Kar
Keyword(s):  
Numerical Simulations ◽  
Basic Reproduction Number ◽  
Goodness Of Fit ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Transmission Dynamics ◽  
Third Wave ◽  
The Third ◽  
The Government ◽  
The Basic Reproduction Number

In this study, we developed a compartmental SIRD model to analyze and forecast the transmission dynamics of the COVID-19 pandemic in Bangladesh during the third wave caused by the Indian delta variant. With the help of the nonlinear system of differential equations, this model can analyze the trends and provide reliable predictions regarding how the epidemic would evolve. The basic reproduction number regarding the pandemic has been determined analytically. The parameters used in this model have been estimated by fitting our model to the reported data for the months of May, June, and July 2021 and the goodness of fit of the parameter’s value has been found by the respective regression coefficients. Further, we conducted a sensitivity analysis of the basic reproduction number and observed that decreasing the transmission rate is the most significant factor in disease prevention. Our proposed model’s appropriateness for the available COVID-19 data in Bangladesh has been demonstrated through numerical simulations. According to the numerical simulation, it is evident that a rise in the transmission rate leads to a significant increase in the infected number of the population. Numerical simulations have also been performed by using our proposed model to forecast the future transmission dynamics for COVID-19 over a longer period of time. Knowledge of these forecasts may help the government in adopting appropriate measures to prepare for unforeseen situations that may arise in Bangladesh as well as to minimize detrimental impacts during the outbreak.

scholarly journals Texas Department of State Health Services' Technical Guidance: Mosquito Abatement Post–Weather Incident

2020 ◽  
Vol 36 (2s) ◽  
pp. 68-73
Author(s):  
Whitney A. Qualls
Keyword(s):  
Health Services ◽  
Severe Weather ◽  
The State ◽  
Background Information ◽  
Local Health ◽  
Guidance Document ◽  
State Health ◽  
Department Of State ◽  
Weather Events ◽  
Texas Department

ABSTRACT The Texas Department of State Health Services provides assistance to local health departments following severe weather events and other public health emergencies. Following the reports of large mosquito populations hindering recovery efforts after Hurricane Harvey, the Texas State Medical Operations Center created the Vector Control Task Force (VCTF) to organize the mosquito response requested through the State of Texas Assistance Requests. Since Hurricane Harvey, there have been other severe weather events that have activated the VCTF. The purpose of this developed document is to provide guidance to local jurisdictions requesting mosquito abatement assistance from the state level in response to a proliferation of nuisance mosquitoes that hinders governmental response and recovery efforts after a severe weather incident. The document also establishes criteria that the VCTF will evaluate to determine if and how resources should be allocated to programs requesting assistance for mosquito abatement. The guidance document provides background information on mosquito surveillance and control and identifies tasks, roles, and responsibilities for local jurisdictions, state, and federal partners.

scholarly journals Community structured model for vaccine strategies to control COVID19 spread: a mathematical study

2021 ◽  
Author(s):  
Elena Aruffo ◽  
Pei Yuan ◽  
Yi Tan ◽  
Evgenia Gatov ◽  
Effie Gournis ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Vaccine Coverage ◽  
Compartment Model ◽  
Effective Vaccine ◽  
Household Transmission ◽  
Waning Immunity ◽  
Vaccine Distribution ◽  
The Impact ◽  
The Basic Reproduction Number

AbstractEfforts to mitigate the COVID-19 pandemic have relied heavily on non-pharmaceutical interventions (NPIs), including physical distancing, hand hygiene, and mask-wearing. However, an effective vaccine is essential to containing the spread of the virus. The first doses were distributed at the end of 2020, but the efficacy, period of immunity it will provide, and percentage of coverage still remain unclear. We developed a compartment model to examine different vaccine strategies for controlling the spread of COVID-19. Our framework accounts for testing rates, test-turnaround times, and vaccination waning immunity. Using reported case data from the city of Toronto, Canada between Mar-Dec, 2020 we defined epidemic phases of infection using contact rates, which depend on individuals’ duration of time spent within the household, workplace/school, or community settings, as well as the probability of transmission upon contact. We investigated the impact of vaccine distribution by comparing different permutations of waning immunity, vaccine coverage and efficacy throughout various stages of NPI’s relaxation in terms of cases, deaths, and household transmission, as measured using the basic reproduction number (R0). We observed that widespread vaccine coverage substantially reduced the number of cases and deaths. In order for NPIs to be relaxed 8 months after vaccine distribution, infection spread can be kept under control with either 60% vaccine coverage, no waning immunity, and 70% efficacy, or with 60% coverage with a 12-month waning immunity and 90% vaccine efficacy. Widespread virus resurgence can result when the immunity wanes under 3 months and/or when NPI’s are relaxed in concomitance with vaccine distribution. In addition to vaccination, our analysis of R0 showed that the basic reproduction number is reduced by decreasing the tests turnaround time and transmission in the household. While we found that household transmission can decrease following the introduction of a vaccine, public health efforts to reduce test turnaround times remain important for virus containment. Our findings suggest that vaccinating two-thirds of the population with a vaccine that is at least 70% effective may be sufficient for controlling COVID-19 spread, as long as NPI’s are not immediately relaxed.

scholarly journals A Comprehensive Assessment of the Associations Between Season of Conception and Birth Defects, Texas, 1999–2015

2020 ◽  
Vol 17 (19) ◽  
pp. 7120
Author(s):  
Elisa Benavides ◽  
Philip J. Lupo ◽  
Peter H. Langlois ◽  
Jeremy M. Schraw
Keyword(s):  
Birth Defects ◽  
Birth Defect ◽  
Hirschsprung Disease ◽  
State Health ◽  
Department Of State ◽  
Texas Department ◽  
Vital Records ◽  
Race Ethnicity ◽  
Using Data ◽  
Prevalence Ratios

Birth defects prevalence may vary seasonally, but previous studies have focused on a few commonly occurring phenotypes. We performed a phenome-wide association study (PheWAS) in order to evaluate the associations between season of conception and a broad range of birth defects. Date of conception was estimated for all livebirths and birth defect cases in Texas from 1999–2015 using data from vital records, provided by the Texas Department of State Health Services Center for Health Statistics. Birth defects diagnoses were obtained from the Texas Birth Defects Registry, a statewide, active surveillance system. We estimated prevalence ratios (PRs) for phenotypes with ≥50 cases according to conception in spring (March-May), summer (June–August) or fall (September–November) relative to winter (December–February), using Poisson regression. Season of conception was associated with 5% of birth defects studied in models adjusted for maternal age, education, race/ethnicity, and number of previous livebirths. Specifically, summer conception was associated with any monitored birth defect (PR 1.03, 95% CI 1.02–1.04) and five specific phenotypes, most notably Hirschsprung disease (PR 1.46, 95% CI 1.22–1.75). These findings suggest that seasonally variable exposures influence the development of several birth defects and may assist in identifying novel environmental risk factors.

scholarly journals District-wise estimation of Basic reproduction number (R0) for COVID-19 in India in the initial phase

2021 ◽  
Author(s):  
Pratip Shil ◽  
Nitin M. Atre ◽  
Avinash A. Patil ◽  
Babasaheb V. Tandale ◽  
Priya Abraham
Keyword(s):  
Basic Reproduction Number ◽  
Initial Phase ◽  
Reproduction Number

scholarly journals Fractional SIR-Model for Estimating Transmission Dynamics of COVID-19 in India

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 86-100
Author(s):  
Nita H. Shah ◽  
Ankush H. Suthar ◽  
Ekta N. Jayswal ◽  
Ankit Sikarwar
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Sir Model ◽  
Time Dependent ◽  
Contact Rate ◽  
Distribution Maps ◽  
Fundamental Parameters ◽  
Different Order ◽  
The Basic Reproduction Number

In this article, a time-dependent susceptible-infected-recovered (SIR) model is constructed to investigate the transmission rate of COVID-19 in various regions of India. The model included the fundamental parameters on which the transmission rate of the infection is dependent, like the population density, contact rate, recovery rate, and intensity of the infection in the respective region. Looking at the great diversity in different geographic locations in India, we determined to calculate the basic reproduction number for all Indian districts based on the COVID-19 data till 7 July 2020. By preparing district-wise spatial distribution maps with the help of ArcGIS 10.2, the model was employed to show the effect of complete lockdown on the transmission rate of the COVID-19 infection in Indian districts. Moreover, with the model's transformation to the fractional ordered dynamical system, we found that the nature of the proposed SIR model is different for the different order of the systems. The sensitivity analysis of the basic reproduction number is done graphically which forecasts the change in the transmission rate of COVID-19 infection with change in different parameters. In the numerical simulation section, oscillations and variations in the model compartments are shown for two different situations, with and without lockdown.

scholarly journals Impact of early detection and vaccination strategy in COVID-19 eradication program in Jakarta, Indonesia

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Dipo Aldila ◽  
Brenda M. Samiadji ◽  
Gracia M. Simorangkir ◽  
Sarbaz H. A. Khosnaw ◽  
Muhammad Shahzad
Keyword(s):  
Mathematical Model ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Vaccination Strategy ◽  
Vaccination Rate ◽  
Rapid Testing ◽  
Social Distancing ◽  
Rapid Spread ◽  
Vaccine Potential ◽  
The Basic Reproduction Number

Abstract Objective Several essential factors have played a crucial role in the spreading mechanism of COVID-19 (Coronavirus disease 2019) in the human population. These factors include undetected cases, asymptomatic cases, and several non-pharmaceutical interventions. Because of the rapid spread of COVID-19 worldwide, understanding the significance of these factors is crucial in determining whether COVID-19 will be eradicated or persist in the population. Hence, in this study, we establish a new mathematical model to predict the spread of COVID-19 considering mentioned factors. Results Infection detection and vaccination have the potential to eradicate COVID-19 from Jakarta. From the sensitivity analysis, we find that rapid testing is crucial in reducing the basic reproduction number when COVID-19 is endemic in the population rather than contact trace. Furthermore, our results indicate that a vaccination strategy has the potential to relax social distancing rules, while maintaining the basic reproduction number at the minimum possible, and also eradicate COVID-19 from the population with a higher vaccination rate. In conclusion, our model proposed a mathematical model that can be used by Jakarta’s government to relax social distancing policy by relying on future COVID-19 vaccine potential.

Sign in / Sign up

Export Citation Format

Share Document