RESUMO
Wolbachia infection in Anopheles albimanus mosquitoes can render mosquitoes less capable of spreading malaria. We developed and analyzed a mechanistic compartmental ordinary differential equation model to evaluate the effectiveness of Wolbachia-based vector control strategies among wild Anopheles mosquitoes in Haiti. The model tracks the mosquito life stages, including egg, larva, and adult (male and female). It also accounts for critical biological effects, such as the maternal transmission of Wolbachia through infected females and cytoplasmic incompatibility, which effectively sterilizes uninfected females when they mate with infected males. We derive and interpret dimensionless numbers, including the basic reproductive number and next-generation numbers. The proposed system presents a backward bifurcation, which indicates a threshold infection that needs to be exceeded to establish a stable Wolbachia infection. The sensitivity analysis ranks the relative importance of the epidemiological parameters at baseline. We simulate different intervention scenarios, including prerelease mitigation using larviciding and thermal fogging before the release, multiple releases of infected populations, and different release times of the year. Our simulations show that the most efficient approach to establishing Wolbachia is to release all the infected mosquitoes immediately after the prerelease mitigation process. Moreover, the model predicts that it is more efficient to release during the dry season than the wet season.
RESUMO
The dynamics of hepatitis C virus (HCV) RNA during translation and replication within infected cells were added to a previous age-structured multiscale mathematical model of HCV infection and treatment. The model allows the study of the dynamics of HCV RNA inside infected cells as well as the release of virus from infected cells and the dynamics of subsequent new cell infections. The model was used to fit in vitro data and estimate parameters characterizing HCV replication. This is the first model to our knowledge to consider both positive and negative strands of HCV RNA with an age-structured multiscale modeling approach. Using this model we also studied the effects of direct-acting antiviral agents (DAAs) in blocking HCV RNA intracellular replication and the release of new virions and fit the model to in vivo data obtained from HCV-infected subjects under therapy.
RESUMO
OBJECTIVE: To evaluate the influence of individual spatial units (ie, counties) on the epidemic spread of foot-and-mouth disease (FMD) virus. SAMPLE POPULATION: 163 counties in Uruguay where there was an outbreak of FMD between April 23 and July 11, 2001. PROCEDURE: A geographically referenced database was created, and the distance between counties (13,203 county pairs), road density of counties (163 counties), and time when cases were reported in those counties (11 weeks of the epidemic) were considered to assess global spatial and spatial-temporal autocorrelation, determine the contribution of links connecting pairs of counties with infected animals, and allow us to hypothesize the influence for spread during the epidemic for counties with greater than the mean infective link contributions. RESULTS: Case clusters were indicated by the Moran Iand Mantel tests during the first 6 weeks of the epidemic. Spatial lags between pairs of counties with infected animals revealed case clustering before and after vaccination was implemented. Temporal lags predicted autocorrelation for up to 3 weeks. Link indices identified counties expected to facilitate epidemic spread. If control measures had been implemented in counties with a high index link (identifiable as early as week 1 of the epidemic), they could have prevented (by week 11 of the epidemic) at least 2.5 times as many cases per square kilometer than the same measures implemented in counties with average link indices. CONCLUSIONS AND CLINICAL RELEVANCE: Analysis of spatial autocorrelation and infective link indices may identify network conditions that facilitate (or prevent) disease spread.