scholarly journals Estimating effects of intervention measures on COVID-19 outbreak in Wuhan taking account of improving diagnostic capabilities using a modelling approach

2020 ◽  
Author(s):  
Jingbo Liang ◽  
Hsiang-Yu Yuan ◽  
Lindsey Wu ◽  
Dirk U. Pfeiffer
Keyword(s):  
Disease Transmission ◽  
Case Definition ◽  
Transmission Dynamics ◽  
Intervention Measures ◽  
Diagnostic Capability ◽  
Peak Transmission ◽  
Diagnostic Capabilities ◽  
The Impact ◽  
Diagnostic Criterion ◽  
Epidemiological Parameters

AbstractBackgroundAlthough by late February 2020 the COVID-19 epidemic was effectively controlled in Wuhan, China, the virus has since spread around the world and been declared a pandemic on March 11. Estimating the effects of interventions, such as transportation restrictions and quarantine measures, on the early COVID-19 transmission dynamics in Wuhan is critical for guiding future virus containment strategies. Since the exact number of COVID-19 infected cases is unknown, the number of documented cases was used by many disease transmission models to infer epidemiological parameters. However, this means that it would not be possible to adequately estimate epidemiological parameters and the effects of intervention measures, because the percentage of all infected cases that were documented changed during the first 2 months of the epidemic as a consequence of a gradually increasing diagnostic capability.MethodsTo overcome the limitations, we constructed a stochastic susceptible-exposed-infected-quarantined-recovered (SEIQR) model, accounting for intervention measures and temporal changes in the proportion of new documented infections out of total new infections, to characterize the transmission dynamics of COVID-19 in Wuhan across different stages of the outbreak. Pre-symptomatic transmission was taken into account in our model, and all epidemiological parameters were estimated using Particle Markov-chain Monte Carlo (PMCMC) method.ResultsOur model captured the local Wuhan epidemic pattern as a two-peak transmission dynamics, with one peak on February 4 and the other on February 12, 2020. The impact of intervention measures determined the timing of the first peak, leading to an 86% drop in the Re from 3.23 (95% CI, 2.22 to 4.20) to 0.45 (95% CI, 0.20 to 0.69). An improved diagnostic capability led to the second peak and a higher proportion of documented infections. Our estimated proportion of new documented infections out of the total new infections increased from 11% (95% CI 1% - 43%) to 28% (95% CI 4% - 62%) after January 26 when more detection kits were released. After the introduction of a new diagnostic criterion (case definition) on February 12, a higher proportion of daily infected cases were documented (49% (95% CI 7% - 79%)).

MODELING CHOLERA TRANSMISSION UNDER DISEASE CONTROL MEASURES

2020 ◽  
pp. 1-26
Author(s):  
MARGARET BROWN ◽  
MIKO JIANG ◽  
CHAYU YANG ◽  
JIN WANG
Keyword(s):  
Disease Control ◽  
Disease Transmission ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Threshold Dynamics ◽  
Education Programs ◽  
Multiple Control ◽  
Indirect Transmission ◽  
Transmission Pathways ◽  
The Impact

We present a new mathematical model to investigate the transmission dynamics of cholera under disease control measures that include education programs and water sanitation. The model incorporates the impact of education programs into the disease transmission rates and that of water sanitation into the environmental pathogen dynamics. We conduct a detailed analysis to the autonomous system of the model and establish the local and global stabilities of its equilibria that characterize the threshold dynamics of cholera. We then perform an optimal control study on the general model with time-dependent controls and explore effective approaches to implement the education programs and water sanitation while balancing their costs. Our analysis and simulation highlight the complex interaction among the direct and indirect transmission pathways of the disease, the intrinsic growth of the environmental pathogen and the impact of multiple control measures, and their roles in collectively shaping the transmission dynamics of cholera.

scholarly journals Joint modelling of serological and hospitalization data reveals that high levels of pre-existing immunity and school holidays shaped the influenza A pandemic of 2009 in The Netherlands

2015 ◽  
Vol 12 (103) ◽  
pp. 20141244 ◽  
Author(s):  
Dennis E. te Beest ◽  
Paul J Birrell ◽  
Jacco Wallinga ◽  
Daniela De Angelis ◽  
Michiel van Boven
Keyword(s):  
The Netherlands ◽  
Disease Transmission ◽  
Influenza A ◽  
Transmission Model ◽  
Cross Sectional ◽  
Intervention Measures ◽  
Probabilistic Classification ◽  
Quantitative Understanding ◽  
Serological Data ◽  
The Impact

Obtaining a quantitative understanding of the transmission dynamics of influenza A is important for predicting healthcare demand and assessing the likely impact of intervention measures. The pandemic of 2009 provides an ideal platform for developing integrative analyses as it has been studied intensively, and a wealth of data sources is available. Here, we analyse two complementary datasets in a disease transmission framework: cross-sectional serological surveys providing data on infection attack rates, and hospitalization data that convey information on the timing and duration of the pandemic. We estimate key epidemic determinants such as infection and hospitalization rates, and the impact of a school holiday. In contrast to previous approaches, our novel modelling of serological data with mixture distributions provides a probabilistic classification of individual samples (susceptible, immune and infected), propagating classification uncertainties to the transmission model and enabling serological classifications to be informed by hospitalization data. The analyses show that high levels of immunity among persons 20 years and older provide a consistent explanation of the skewed attack rates observed during the pandemic and yield precise estimates of the probability of hospitalization per infection (1–4 years: 0.00096 (95%CrI: 0.00078–0.0012); 5–19 years: 0.00036 (0.00031–0.0044); 20–64 years: 0.0015 (0.00091–0.0020); 65+ years: 0.0084 (0.0028–0.016)). The analyses suggest that in The Netherlands, the school holiday period reduced the number of infectious contacts between 5- and 9-year-old children substantially (estimated reduction: 54%; 95%CrI: 29–82%), thereby delaying the unfolding of the pandemic in The Netherlands by approximately a week.

Mathematical modeling of the impact of temperature variations and immigration on malaria prevalence in Nigeria

2021 ◽  
pp. 2150067
Author(s):  
Eunice E. Ukwajunor ◽  
Eno E. E. Akarawak ◽  
Israel Olutunji Abiala
Keyword(s):  
Equilibrium Point ◽  
Disease Transmission ◽  
Deterministic Model ◽  
Malaria Incidence ◽  
Malaria Prevalence ◽  
Endemic Equilibrium ◽  
Transmission Dynamics ◽  
Marginal Effect ◽  
Asymptotically Stable ◽  
The Impact

The study examines the population-level impact of temperature variability and immigration on malaria prevalence in Nigeria, using a novel deterministic model. The model incorporates disease transmission by immigrants into the community. In the absence of immigration, the model is shown to exhibit the phenomenon of backward bifurcation. The disease-free equilibrium of the autonomous version of the model was found to be locally asymptotically stable in the absence of infective immigrants. However, the model exhibits an endemic equilibrium point when the immigration parameter is greater than zero. The endemic equilibrium point is seen to be globally asymptotically stable in the absence of disease-induced mortality. Uncertainty and sensitivity analysis of the model, using parameter values and ranges relevant to malaria transmission dynamics in Nigeria, shows that the top three parameters that drive malaria prevalence (with respect to [Formula: see text]) are the mosquito natural death rate ([Formula: see text]), mosquito biting rate ([Formula: see text]) and the transmission rates between humans and mosquitoes ([Formula: see text]). Numerical simulations of the model show that in Nigeria, malaria burden increases with increasing mean monthly temperature in the range of 22–28[Formula: see text]. Thus, this study suggests that control strategies for malaria should be intensified during this period. It is further shown that the proportion of infective immigrants has marginal effect on the transmission dynamics of the disease. Therefore, the simulations suggest that a reduction in the fraction of infective immigrants, either exposed or infectious, would significantly reduce the malaria incidence in a population.

scholarly journals INFEKTA—An agent-based model for transmission of infectious diseases: The COVID-19 case in Bogotá, Colombia

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245787
Author(s):  
Jonatan Gomez ◽  
Jeisson Prieto ◽  
Elizabeth Leon ◽  
Arles Rodríguez
Keyword(s):  
Infectious Diseases ◽  
Disease Transmission ◽  
Computational Models ◽  
Compartmental Model ◽  
Transmission Dynamics ◽  
Agent Based Model ◽  
Agent Based ◽  
Social Distancing ◽  
The Impact ◽  
The Town

The transmission dynamics of the coronavirus—COVID-19—have challenged humankind at almost every level. Currently, research groups around the globe are trying to figure out such transmission dynamics under special conditions such as separation policies enforced by governments. Mathematical and computational models, like the compartmental model or the agent-based model, are being used for this purpose. This paper proposes an agent-based model, called INFEKTA, for simulating the transmission of infectious diseases, not only the COVID-19, under social distancing policies. INFEKTA combines the transmission dynamic of a specific disease, (according to parameters found in the literature) with demographic information (population density, age, and genre of individuals) of geopolitical regions of the real town or city under study. Agents (virtual persons) can move, according to its mobility routines and the enforced social distancing policy, on a complex network of accessible places defined over an Euclidean space representing the town or city. The transmission dynamics of the COVID-19 under different social distancing policies in Bogotá city, the capital of Colombia, is simulated using INFEKTA with one million virtual persons. A sensitivity analysis of the impact of social distancing policies indicates that it is possible to establish a ‘medium’ (i.e., close 40% of the places) social distancing policy to achieve a significant reduction in the disease transmission.

scholarly journals Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves

2021 ◽  
Author(s):  
Bo Huang ◽  
Jionghua Wang ◽  
Jixuan Cai ◽  
Shiqi Yao ◽  
Paul Kay Sheung CHAN ◽  
...  
Keyword(s):  
Population Density ◽  
Disease Transmission ◽  
Reproduction Number ◽  
Social Contact ◽  
Preventive Interventions ◽  
Population Densities ◽  
Social Contacts ◽  
Intervention Measures ◽  
The Impact ◽  
Mobility Reduction

Abstract COVID-19 resurgences worldwide have posed significant challenges to the formulation of preventive interventions, especially given that the effects of physical distancing and upcoming vaccines on reducing susceptible social contacts and eventually halting transmission are still unclear. Using anonymized mobile geolocation data in China, we devised a mobility-associated social contact index to quantify the impact of both physical distancing and vaccination measures in a unified way such that the gap between intervention measures and disease transmission can be explicitly bridged. This index explained 90% of the variance in the changing reproduction number of infections across the COVID-19 outbreak in Wuhan, and was validated in six other cities of different population densities. Our simulations showed that vaccination combined with physical distancing can contain resurgences without relying on mobility reduction, whereas a gradual vaccination process alone cannot achieve this. Further, for cities with medium-population density, vaccination can shorten the duration of physical distancing by 36%-78%, whereas for cities with high-population density, infection numbers can well be controlled through moderate physical distancing. These findings provide guidance on tailoring and implementing comprehensive interventions for cities with varying population densities.

scholarly journals Modelling the transmission dynamics of Theileria annulata: model structure and validation for the Turkish context

Parasitology ◽  
2012 ◽  
Vol 139 (4) ◽  
pp. 441-453 ◽  
Author(s):  
A. J. SUTTON ◽  
T. KARAGENC ◽  
S. BAKIRCI ◽  
H. SARALI ◽  
G. PEKEL ◽  
...  
Keyword(s):  
Compartmental Model ◽  
Tick Infestation ◽  
Theileria Annulata ◽  
Transmission Dynamics ◽  
Tick Population ◽  
Temporal Separation ◽  
Intervention Measures ◽  
Tick Attachment ◽  
Using Data ◽  
The Impact

SUMMARYA mathematical model that describes the transmission dynamics of Theileria annulata is proposed that consists of 2 host components: the Hyalomma tick population and a compartmental model of T. annulata infection in the cattle population. The model was parameterized using data describing tick infestation and the infection status of cattle in Turkey from 2006 to 2008. The tick attachment rates are highly seasonal and because of the temporal separation of infectious and susceptible ticks virtually all ticks are infected by carrier cattle, so that annual peaks of disease in cattle do not impact on infection in the Hyalomma tick population. The impact of intervention measures that target the tick population both on the host and in the environment and their impact on the transmission of T. annulata were investigated. Interventions that have a limited ‘one-off’ impact and interventions that have a more permanent impact were both considered. The results from the model show the importance of targeting ticks during the period when they have left their first host as nymphs but have yet to feed on their second host.

scholarly journals Analyzing the Effects of Temperature and Human Movement on Malaria Disease Transmission Dynamics

2020 ◽  
Author(s):  
Ganga Ram Phaijoo
Keyword(s):  
Disease Transmission ◽  
Human Movement ◽  
Transmission Dynamics ◽  
Vector Borne Diseases ◽  
Movement Rates ◽  
Anopheles Mosquitoes ◽  
Vector Borne ◽  
Temperature Levels ◽  
Global And Local ◽  
The Impact

Abstract Background: Malaria disease is transmitted by the bite of Anopheles mosquitoes. Plasmodium parasites are responsible for the disease. Due to human movement from one place to the other, vector borne diseases like malaria are spreading rapidly throughout the world. They have become major causes of morbidity and mortality worldwide. Changing temperature levels has significant impact on the life cycle, biting behavior and death rates of the mosquitoes which can transmit the disease.Methods: A multi patch SEIRS - SEI deterministic compartmental model for malaria disease is developed to study the disease transmission dynamics. The impact of temperature and human movement in transmission dynamics is investigated. Both global and local basic reproduction numbers are computed for two patches in two patch setting.Results: Disease free equilibrium is locally stable when the basic reproduction number is less than unity and unstable when the number is greater than unity. Numerical results show that the prevalence of the disease changes with the change in human movement rates between the patches; temperature affects the transmission dynamics of malaria disease.Conclusion: The burden of malaria disease can be reduced by managing the host movement between low and high disease prevalent patches. The optimal temperature for malaria disease transmission is 25 °C.

Climate-dependent malaria disease transmission model and its analysis

2019 ◽  
Vol 12 (08) ◽  
pp. 1950087
Author(s):  
Kassahun Workalemahu Gashaw ◽  
Semu Mitiku Kassa ◽  
Rachid Ouifki
Keyword(s):  
Periodic System ◽  
Disease Transmission ◽  
Periodic Variation ◽  
Climate Variation ◽  
Transmission Dynamics ◽  
Threshold Function ◽  
Transmission Model ◽  
Basic Reproduction Ratio ◽  
Reproduction Ratio ◽  
The Impact

Malaria infection continues to be a major problem in many parts of the world including Africa. Environmental variables are known to significantly affect the population dynamics and abundance of insects, major catalysts of vector-borne diseases, but the exact extent and consequences of this sensitivity are not yet well established. To assess the impact of the variability in temperature and rainfall on the transmission dynamics of malaria in a population, we propose a model consisting of a system of non-autonomous deterministic equations that incorporate the effect of both temperature and rainfall to the dispersion and mortality rate of adult mosquitoes. The model has been validated using epidemiological data collected from the western region of Ethiopia by considering the trends for the cases of malaria and the climate variation in the region. Further, a mathematical analysis is performed to assess the impact of temperature and rainfall change on the transmission dynamics of the model. The periodic variation of seasonal variables as well as the non-periodic variation due to the long-term climate variation have been incorporated and analyzed. In both periodic and non-periodic cases, it has been shown that the disease-free solution of the model is globally asymptotically stable when the basic reproduction ratio is less than unity in the periodic system and when the threshold function is less than unity in the non-periodic system. The disease is uniformly persistent when the basic reproduction ratio is greater than unity in the periodic system and when the threshold function is greater than unity in the non-periodic system.

scholarly journals Seasonal Variations and Immune Responses: Any Succor for COVID-19 Pandemic in Nigeria

2020 ◽  
Author(s):  
Adeleye Adeshakin ◽  
Oluwamuyiwa Ayanshina ◽  
Lukman Afolabi ◽  
Funmilayo Adeshakin ◽  
Ganiyu Alli-Balogun ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Seasonal Variations ◽  
Disease Transmission ◽  
Weather Conditions ◽  
Transmission Dynamics ◽  
Infectious Disease Transmission ◽  
Healthcare Facilities ◽  
Weather Changes ◽  
The Impact

There is a global rise in the emergence of infectious diseases and the enigmatic coronavirus disease 2019 (COVID-19) being the most recent one. It is ravaging the world with little understanding of its etiology and factors affecting its transmission dynamics. Meanwhile, seasonal variations in weather are major factors impacting infectious disease transmission patterns. Developing countries are likely to be most affected by weather changes, largely because of challenges such as inadequate drainage and sewage management systems, healthcare facilities, education, and funding to efficiently mitigate infectious diseases. In Nigeria, weather conditions alternate between rainy and dry seasons. Conditions such as rainfall, flood, and humidity have been reported to influence infectious disease transmission. Thus, understanding the impact of weather changes in transmission dynamics and immune response to COVID 19 will help in preventive measures and policy making to curtail its spread most especially in Nigeria as the rainy season fully sets in.

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