Mathematical Model of the Role of Asymptomatic Infection in Outbreaks of Some Emerging Pathogens

Preparation for outbreaks of emerging infectious diseases is often predicated on beliefs that we will be able to understand the epidemiological nature of an outbreak early into its inception. However, since many rare emerging diseases exhibit different epidemiological behaviors from outbreak to outbreak, early and accurate estimation of the epidemiological situation may not be straightforward in all cases. Previous studies have proposed considering the role of active asymptomatic infections co-emerging and co-circulating as part of the process of emergence of a novel pathogen. Thus far, consideration of the role of asymptomatic infections in emerging disease dynamics have usually avoided considering some important sets of influences. In this paper, we present and analyze a mathematical model to explore the hypothetical scenario that some (re)emerging diseases may actually be able to maintain stable, endemic circulation successfully in an entirely asymptomatic state. We argue that an understanding of this potential mechanism for diversity in observed epidemiological dynamics may be of considerable importance in understanding and preparing for outbreaks of novel and/or emerging diseases

Mathematical Modelling of Mosquito Dispersal in a Heterogeneous Environment.

Mosquito dispersal is a key behavioural factor that affects the persistence and resurgence of several vector-borne diseases. Spatial heterogeneity of mosquito resources, such as hosts and breeding sites, affects mosquito dispersal behaviour and consequently affects mosquito population structures, human exposure to vectors, and the ability to control disease transmission. In this paper, we develop and simulate a discrete-space continuous-time mathematical model to investigate the impact of dispersal and heterogeneous distribution of resources on the distribution and dynamics of mosquito populations. We build an ordinary differential equation model of the mosquito life cycle and replicate it across a hexagonal grid (multi-patch system) that represents two-dimensional space. We use the model to estimate mosquito dispersal distances and to evaluate the effect of spatial repellents as a vector control strategy. We find evidence of association between heterogeneity, dispersal, spatial distribution of resources, and mosquito population dynamics. Random distribution of repellents reduces the distance moved by mosquitoes, offering a promising strategy for disease control

Mathematical Model of the Role of Asymptomatic Infection in Outbreaks of Some Emerging Pathogens

Preparation for outbreaks of emerging infectious diseases is often predicated on beliefs that we will be able to understand the epidemiological nature of an outbreak early into its inception. However, since many rare emerging diseases exhibit different epidemiological behaviors from outbreak to outbreak, early and accurate estimation of the epidemiological situation may not be straightforward in all cases. Previous studies have proposed considering the role of active asymptomatic infections co-emerging and co-circulating as part of the process of emergence of a novel pathogen. Thus far, consideration of the role of asymptomatic infections in emerging disease dynamics have usually avoided considering some important sets of influences. In this paper, we present and analyze a mathematical model to explore the hypothetical scenario that some (re)emerging diseases may actually be able to maintain stable, endemic circulation successfully in an entirely asymptomatic state. We argue that an understanding of this potential mechanism for diversity in observed epidemiological dynamics may be of considerable importance in understanding and preparing for outbreaks of novel and/or emerging diseases

Unequal effects of SARS-CoV-2 infections: model of SARS-CoV-2 dynamics in Cameroon (Sub-Saharan Africa) versus New York State (United States)

Worldwide, the recent SARS-CoV-2 virus disease outbreak has infected more than 691,000,000 people and killed more than 6,900,000. Surprisingly, Sub-Saharan Africa has suffered the least from the SARS-CoV-2 pandemic. Factors that are inherent to developing countries and that contrast with their counterparts in developed countries have been associated with these disease burden differences. In this paper, we developed data-driven COVID-19 mathematical models of two ‘extreme’: Cameroon, a developing country, and New York State (NYS) located in a developed country. We then identified critical parameters that could be used to explain the lower-than-expected COVID-19 disease burden in Cameroon versus NYS and to help mitigate future major disease outbreaks. Through the introduction of a ‘disease burden’ function, we found that COVID-19 could have been much more severe in Cameroon than in NYS if the vaccination rate had remained very low in Cameroon and the pandemic had not ended

Synergy map for drugs IFN-<i>α</i> and adefovir in HBV.

<p>The horizontal axes scale the dose of IFN-<i>α</i> and the vertical axes scale the dose of adefovir. The color maps represent the synergies between the two drugs IFN-<i>α</i> and adefovir in reducing the level of scar density (A) and the viral load (B) at day 180 of infection.</p

Efficacy map in combination therapy with IFN-<i>α</i> and adefovir.

<p>The horizontal axes scale the fractions for the dose of IFN-<i>α</i> and the vertical axes scale the fractions for the dose of adefovir. The color maps represent the efficacies of reduction in the level of scar density (A) and the viral load (B) at day 180 of infection.</p

Variables of the model.

<p>All densities and concentrations are in units of g/cm³.</p

Diagram of interactions between cells, virus and cytokines in hepatitis B.

<p>Diagram of interactions between cells, virus and cytokines in hepatitis B.</p

Monotherapy and combination therapy with intermittent IFN-<i>α</i> and continuous adefovir.

<p>The horizontal axes scale the time in days and the vertical axes scale the average densities in g/cm³ for all the variables for the first 180 days since the start of the disease, in control case (blue) and with treatment (IFN-<i>α</i>–orange, adefovir–blue and combination–red).</p

Bumble bee pollination and the wildflower/crop trade-off: When do wildflower enhancements improve crop yield?

No abstract available