The Basic Reproduction Number Obtained From Jacobian And Next Generation Matrices - A Case Study Of Dengue Transmission Modelling.

The basic reproduction number is a key parameter in mathematical modelling of transmissible diseases. From the stability analysis of the disease free equilibrium, by applying Routh-Hurwitz criteria, a threshold is obtained, which is called the basic reproduction number. However, the application of spectral radius theory on the next generation matrix provides a different expression for the basic reproduction number, that is, the square root of the previously found formula. If the spectral radius of the next generation matrix is defined as the geometric mean of partial reproduction numbers, however the product of these partial numbers is the basic reproduction number, then both methods provide the same expression. In order to show this statement, dengue transmission modelling incorporating or not the transovarian transmission is considered as a case study. Also tuberculosis transmission and sexually transmitted infection modellings are taken as further examples.

On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata

We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.

Vectorial capacity, basic reproduction number, force of infection and all that: formal notation to complete and adjust their classical concepts and equations

A dimensional analysis of the classical equations related to the dynamics of vector-borne infections is presented. It is provided a formal notation to complete the expressions for the Ross' Threshold Theorem, the Macdonald's basic reproduction "rate" and sporozoite "rate", Garret-Jones' vectorial capacity and Dietz-Molineaux-Thomas' force of infection. The analysis was intended to provide a formal notation that complete the classical equations proposed by these authors.

On estimating the basic reproduction number in distinct stages of a contagious disease spreading

In epidemiology, the basic reproduction number R-0 is usually defined as the average number of new infections caused by a single infective individual introduced into a completely susceptible population. According to this definition. R-0 is related to the initial stage of the spreading of a contagious disease. However, from epidemiological models based on ordinary differential equations (ODE), R-0 is commonly derived from a linear stability analysis and interpreted as a bifurcation parameter: typically, when R-0 >1, the contagious disease tends to persist in the population because the endemic stationary solution is asymptotically stable: when R-0 <1, the corresponding pathogen tends to naturally disappear because the disease-free stationary solution is asymptotically stable. Here we intend to answer the following question: Do these two different approaches for calculating R-0 give the same numerical values? In other words, is the number of secondary infections caused by a unique sick individual equal to the threshold obtained from stability analysis of steady states of ODE? For finding the answer, we use a susceptibleinfective-recovered (SIR) model described in terms of ODE and also in terms of a probabilistic cellular automaton (PCA), where each individual (corresponding to a cell of the PCA lattice) is connected to others by a random network favoring local contacts. The values of R-0 obtained from both approaches are compared, showing good agreement. (C) 2012 Elsevier B.V. All rights reserved.

Vectorial capacity, basic reproduction number, force of infection and all that: formal notation to complete and adjust their classical concepts and equations

A dimensional analysis of the classical equations related to the dynamics of vector-borne infections is presented. It is provided a formal notation to complete the expressions for the Ross' threshold theorem, the Macdonald's basic reproduction "rate" and sporozoite "rate", Garret-Jones' vectorial capacity and Dietz-Molineaux-Thomas' force of infection. The analysis was intended to provide a formal notation that complete the classical equations proposed by these authors.

Estimating the basic reproductive number from viral sequence data.

Epidemiological processes leave a fingerprint in the pattern of genetic structure of virus populations. Here, we provide a new method to infer epidemiological parameters directly from viral sequence data. The method is based on phylogenetic analysis using a birth-death model (BDM) rather than the commonly used coalescent as the model for the epidemiological transmission of the pathogen. Using the BDM has the advantage that transmission and death rates are estimated independently and therefore enables for the first time the estimation of the basic reproductive number of the pathogen using only sequence data, without further assumptions like the average duration of infection. We apply the method to genetic data of the HIV-1 epidemic in Switzerland.

Estimating the Reproduction Number of Ebola Virus (EBOV) During the 2014 Outbreak in West Africa

The 2014 Ebola virus (EBOV) outbreak in West Africa is the largest outbreak of the genus Ebolavirus to date. To better understand the spread of infection in the affected countries, it is crucial to know the number of secondary cases generated by an infected index case in the absence and presence of control measures, i.e., the basic and effective reproduction number. In this study, I describe the EBOV epidemic using an SEIR (susceptible-exposed-infectious-recovered) model and fit the model to the most recent reported data of infected cases and deaths in Guinea, Sierra Leone and Liberia. The maximum likelihood estimates of the basic reproduction number are 1.51 (95% confidence interval [CI]: 1.50-1.52) for Guinea, 2.53 (95% CI: 2.41-2.67) for Sierra Leone and 1.59 (95% CI: 1.57-1.60) for Liberia. The model indicates that in Guinea and Sierra Leone the effective reproduction number might have dropped to around unity by the end of May and July 2014, respectively. In Liberia, however, the model estimates no decline in the effective reproduction number by end-August 2014. This suggests that control efforts in Liberia need to be improved substantially in order to stop the current outbreak.

Rapid drop in the reproduction number during the Ebola outbreak in the Democratic Republic of Congo.

The Democratic Republic of Congo (DRC) experienced a confined rural outbreak of Ebola virus disease (EVD) with 69 reported cases from July to October 2014. Understanding the transmission dynamics during the outbreak can provide important information for anticipating and controlling future EVD epidemics. I fitted an EVD transmission model to previously published data of this outbreak and estimated the basic reproduction number R 0 = 5.2 (95% CI [4.0-6.7]). The model suggests that the net reproduction number Rt fell below unity 28 days (95% CI [25-34] days) after the onset of symptoms in the index case. This study adds to previous epidemiological descriptions of the 2014 EVD outbreak in DRC, and is consistent with the notion that a rapid implementation of control interventions helped reduce further spread.

Malpighiaceae: correlations between habit, fruit type and basic chromosome number

The family Malpighiaceae presents species with different habits, fruit types and cytological characters. Climbers are considered the most derived habit, followed, respectively, by the shrubby and arboreal ones. The present study examines the relationship between basic chromosome numbers and the derivation of climbing habit and fruit types in Malpighiaceae. A comparison of all the chromosome number reports for Malpighiaceae showed a predominance of chromosome numbers based on x=5 or 10 in the genera of sub-family Malpighioideae, mainly represented by climbers with winged fruits, whereas non-climbing species with non-winged fruits, which predominate in sub-family Byrsonimoideae, had counts based on x=6, which is considered the less derived basic number for the family. Based on such data, confirmed by statistic assays, and on the monophyletic origin of this family, we admit the hypothesis that morphological derivation of habit and fruit is correlated with chromosome basic number variation in the family Malpighiaceae.

On the time to reach a critical number of infections in epidemic models with infective and susceptible immigrants.

In this paper we examine the time T to reach a critical number K0 of infections during an outbreak in an epidemic model with infective and susceptible immigrants. The underlying process X, which was first introduced by Ridler-Rowe (1967), is related to recurrent diseases and it appears to be analytically intractable. We present an approximating model inspired from the use of extreme values, and we derive formulae for the Laplace-Stieltjes transform of T and its moments, which are evaluated by using an iterative procedure. Numerical examples are presented to illustrate the effects of the contact and removal rates on the expected values of T and the threshold K0, when the initial time instant corresponds to an invasion time. We also study the exact reproduction number Rexact,0 and the population transmission number Rp, which are random versions of the basic reproduction number R0.

A hypothesis for explaining single outbreaks (like the Black Death in European cities) of vector-borne infections

We propose a mechanism by which single outbreaks of vector-borne infections can happen even when the value of the basic reproduction number, R(o), of the infection is below one. With this hypothesis we have shown that dynamical models simulations demonstrate that the arrival of a relatively small (with respect to the host population) number of infected vectors can trigger a short-lived epidemic but with a huge number of cases. These episodes are characterized by a sudden outbreak in a previously virgin area that last from weeks to a few months, and then disappear without leaving vestiges. The hypothesis proposed in this paper to explain those single outbreaks of vector-borne infections, even when total basic reproduction number, Ro, is less than one (which explain the fact that those infections fail to establish themselves at endemic levels), is that the vector-to-host component of Ro is greater than one and that a sufficient amount of infected vectors are imported to the vulnerable area, triggering the outbreak. We tested the hypothesis by performing numerical simulations that reproduce the observed outbreaks of chikungunya in Italy in 2007 and the plague in Florence in 1348. The theory proposed provides an explanation for isolated outbreaks of vector-borne infections, ways to calculate the size of those outbreaks from the number of infected vectors arriving in the affected areas. Given the ever-increasing worldwide transportation network, providing a high degree of mobility from endemic to virgin areas, the proposed mechanism may have important implications for public health planning. (C) 2009 Elsevier Ltd. All rights reserved.

Cost-effectiveness analysis of a hypothetical hepatitis C vaccine compared to antiviral therapy

We propose a mathematical model to simulate the dynamics of hepatitis C virus (HCV) infection in the state of Sao Paulo, Brazil. We assumed that a hypothetical vaccine, which cost was taken to be the initial cost of the vaccine against hepatitis B exists and it is introduced in the model. We computed its cost-effectiveness compared with the anti-HCV therapy. The calculated basic reproduction number was 1.20. The model predicts that without intervention a steady state exists with an HCV prevalence of 3%, in agreement with the Current epidemiological data. Starting from this steady state three interventions were simulated: indiscriminate vaccination, selective vaccination and anti-HCV therapy. Selective vaccination proved to be the strategy with the best cost-effectiveness ratio, followed by indiscriminate vaccination and anti-HCV therapy.

The risk of chikungunya fever in a dengue-endemic area

Background. Chikungunya, an alphavirus of the Togaviridae family, causes a febrile disease transmitted to humans by the bite of infected Aedes mosquitoes. This infection is reaching endemic levels in many Southeast Asian countries. Symptoms include sudden onset of fever, chills, headache, nausea, vomiting, joint pain with or without swelling, low back pain, and rash. According to the World Health Organization, there are 2 billion people living in Aedes-infested areas. In addition, traveling to these areas is popular, making the potential risk of infections transmitted by the bite of infected Aedes mosquitoes very high. Methods. We proposed a mathematical model to estimate the risk of acquiring chikungunya fever in an Aedes-infested area by taking the prevalence of dengue fever into account. The basic reproduction number for chikungunya fever R-0chik can be written as a function of the basic reproduction number of dengue R-0dengue by calculating the ratio R-0chik/R-0dengue. From R-0chik, we estimated the force of infection and the risk of acquiring the disease both for local residents of a dengue-endemic area and for travelers to this area. Results. We calculated that R-0chik is 64.4% that of R-0dengue. The model was applied to a hypothetical situation, namely, estimating the individual risk of acquiring chikungunya fever in a dengue-endemic area, both for local inhabitants (22% in steady state) and for visiting travelers (from 0.31% to 1.23% depending on the time spent in the area). Conclusions. The method proposed based on the output of a dynamical model is innovative and provided an estimation of the risk of infection, both for local inhabitants and for visiting travelers.

Estimation of R(0) from the initial phase of an outbreak of a vector-borne infection

The magnitude of the basic reproduction ratio R(0) of an epidemic can be estimated in several ways, namely, from the final size of the epidemic, from the average age at first infection, or from the initial growth phase of the outbreak. In this paper, we discuss this last method for estimating R(0) for vector-borne infections. Implicit in these models is the assumption that there is an exponential phase of the outbreaks, which implies that in all cases R(0) > 1. We demonstrate that an outbreak is possible, even in cases where R(0) is less than one, provided that the vector-to-human component of R(0) is greater than one and that a certain number of infected vectors are introduced into the affected population. This theory is applied to two real epidemiological dengue situations in the southeastern part of Brazil, one where R(0) is less than one, and other one where R(0) is greater than one. In both cases, the model mirrors the real situations with reasonable accuracy.

Dengue and the risk of urban yellow fever reintroduction in São Paulo State, Brazil

OBJECTIVE: To propose a mathematical method for the estimation of the Basic Reproduction Number, R0, of urban yellow fever in a dengue-infested area. METHODS: The method is based on the assumption that, as the same vector (Aedes aegypti) causes both infections, all the quantities related to the mosquito, estimated from the initial phase of dengue epidemic, could be applied to yellow fever dynamics. It is demonstrated that R0 for yellow fever is, on average, 43% lower than that for dengue. This difference is due to the longer dengue viremia and its shorter extrinsic incubation period. RESULTS: In this study the analysis was expanded to the epidemiological situation of dengue in São Paulo in the year 2001. The total number of dengue cases increased from 3,582 in 2000 to 51,348 in 2001. It was then calculated R0 for yellow fever for every city which have shown R0 of dengue greater than 1. It was also estimated the total number of unprotected people living in highly risky areas for urban yellow fever. CONCLUSIONS: Currently there is a great number of non-vaccinated people living in Aedes aegypti infested area in the state of São Paulo.