ABSTRACT
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.
Subject(s)
Animals , Humans , Basic Reproduction Number , Disease Transmission, Infectious , Insect Vectors , Models, BiologicalABSTRACT
Epidemiological parameters, such as age-dependent force of infection and average age at infection (
) were estimated for rubella, varicella, rotavirus A, respiratory syncytial virus, hepatitis A and parvovirus B19 infections for a non-immunized Brazilian community, using the same sera samples. The for the aforementioned diseases were 8.45 years (yr) [95 percent CI: (7.23, 9.48) yr], 3.90 yr [95 percent CI: (3.51, 4.28) yr], 1.03 yr [95 percent CI: (0.96, 1.09) yr], 1.58 yr [95 percent CI: (1.39, 1.79) yr], 7.17 yr [95 percent CI: (6.48, 7.80) yr] and 7.43 yr [95 percent CI: (5.68, 9.59) yr], respectively. The differences between average ages could be explained by factors such as differences in the effectiveness of the protection conferred to newborns by maternally derived antibodies, competition between virus species and age-dependent host susceptibility. Our seroprevalence data may illustrate a case of the above-mentioned mechanisms working together within the same population.
Subject(s)
Adolescent , Adult , Child , Child, Preschool , Humans , Infant , Infant, Newborn , Young Adult , Virus Diseases/epidemiology , Brazil/epidemiology , Monte Carlo Method , Prevalence , Seroepidemiologic Studies , Virus Diseases/immunology , Young AdultABSTRACT
We analyzed dengue incidence in the period between October 2006-July 2007 of 146 cities around the country were Larval Index Rapid Assay (LIRA) surveillance was carried out in October 2006. Of these, we chosen 61 cities that had 500 or more cases reported during this period. We calculated the incidence coefficient, the force of infection (¼) and the basic reproduction number (R0) of dengue in those 61 cities and correlated those variables with the LIRA. We concluded that ¼ and R0 are more associated with the number of cases than LIRA. In addition, the average R0 for the 2006/2007 dengue season was almost as high as that calculated for the 2001/2002 season, the worst in Brazilian history.