Estimating the number of unvaccinated Chinese workers against yellow fever in Angola

Background: A yellow fever epidemic occurred in Angola in 2016 with 884 laboratory confirmed cases and 373 deaths. Eleven unvaccinated Chinese nationals working in Angola were also infected and imported the disease to China, thereby presenting the first importation of yellow fever into Asia. In Angola, there are about 259,000 Chinese foreign workers. The fact that 11 unvaccinated Chinese workers acquired yellow fever suggests that many more Chinese workers in Angola were not vaccinated. Methods: We applied a previously developed model to back-calculate the number of unvaccinated Chinese workers in Angola in order to determine the extent of lack of vaccine coverage. Results: Our models suggest that none of the 259,000 Chinese had been vaccinated, although yellow fever vaccination is mandated by the International Health Regulations. Conclusion: Governments around the world including China need to ensure that their citizens obtain YF vaccination when traveling to countries where such vaccines are required in order to prevent the international spread of yellow fever

MODELING the INTERACTION BETWEEN AIDS and TUBERCULOSIS

A deterministic model is proposed for the study of the dynamics of acquired immunodeficiency syndrome (AIDS) and tuberculosis (TB) co-infection. the model is comprised by a set of sixteen ordinary differential equations representing different states of both diseases, and it is intended to provide a theoretical framework for the study of the interaction between both infections. Numerical simulations of the model resulted in three striking outcomes: first, the pathogenicity of Human Immunodeficiency Virus (HIV) is enhanced by the presence of TB, and vice-versa; second, the prevalence of AIDS is higher in the presence of TB; and third, relative risk analysis demonstrated a much stronger influence of AIDS on TB than the other way around.ESCOLA PAULISTA MED,BR-04023 São Paulo,BRAZILUNIV São Paulo,INST PHYS,São Paulo,BRAZILHCFMUSP,BR-01246 São Paulo,BRAZILESCOLA PAULISTA MED,BR-04023 São Paulo,BRAZILWeb of Scienc

How doctors diagnose diseases and prescribe treatments: an fMRI study of diagnostic salience

Understanding the brain mechanisms involved in diagnostic reasoning may contribute to the development of methods that reduce errors in medical practice. In this study we identified similar brain systems for diagnosing diseases, prescribing treatments, and naming animals and objects using written information as stimuli. Employing time resolved modeling of blood oxygen level dependent (BOLD) responses enabled time resolved (400 milliseconds epochs) analyses. With this approach it was possible to study neural processes during successive stages of decision making. Our results showed that highly diagnostic information, reducing uncertainty about the diagnosis, decreased monitoring activity in the frontoparietal attentional network and may contribute to premature diagnostic closure, an important cause of diagnostic errors. We observed an unexpected and remarkable switch of BOLD activity within a right lateralized set of brain regions related to awareness and auditory monitoring at the point of responding. We propose that this neurophysiological response is the neural substrate of awareness of one’s own (verbal) response. Our results highlight the intimate relation between attentional mechanisms, uncertainty, and decision making and may assist the advance of approaches to prevent premature diagnostic closure

Dynamics of the 2006/2007 dengue outbreak in Brazil

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 (») and the basic reproduction number (R0) of dengue in those 61 cities and correlated those variables with the LIRA. We concluded that » 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.CNPqFAPESPFMUSP - H

Magnitude and frequency variations of vector-borne infection outbreaks using the Ross–Macdonald model : explaining and predicting outbreaks of dengue fever

The classical Ross–Macdonald model is often utilized to model vector-borne infections; however, this model fails on several fronts. First, using measured (or estimated) parameters, which values are accepted from the literature, the model predicts a much greater number of cases than what is usually observed. Second, the model predicts a single large outbreak that is followed by decades of much smaller outbreaks, which is not consistent with what is observed. Usually towns or cities report a number of recurrences for many years, even when environmental changes cannot explain the disappearance of the infection between the peaks. In this paper, we continue to examine the pitfalls in modelling this class of infections, and explain that, if properly used, the Ross–Macdonald model works and can be used to understand the patterns of epidemics and even, to some extent, be used to make predictions.We model several outbreaks of dengue fever and show that the variable pattern of yearly recurrence (or its absence) can be understood and explained by a simple Ross–Macdonald model modified to take into account human movement across a range of neighbourhoods within a city. In addition, we analyse the effect of seasonal variations in the parameters that determine the number, longevity and biting behaviour of mosquitoes. Based on the size of the first outbreak, we show that it is possible to estimate the proportion of the remaining susceptible individuals and to predict the likelihood and magnitude of the eventual subsequent outbreaks. This approach is described based on actual dengue outbreaks with different recurrence patterns from some Brazilian regions

Inhibition of Toll-Like Receptor 4 Signaling Mitigates Microvascular Loss but Not Fibrosis in a Model of Ischemic Acute Kidney Injury

The development of chronic kidney disease (CKD) following an episode of acute kidney injury (AKI) is an increasingly recognized clinical problem. Inhibition of toll-like receptor 4 (TLR4) protects renal function in animal models of AKI and has become a viable therapeutic strategy in AKI. However, the impact of TLR4 inhibition on the chronic sequelae of AKI is unknown. Consequently, we examined the chronic effects of TLR4 inhibition in a model of ischemic AKI. Mice with a TLR4-deletion on a C57BL/6 background and wild-type (WT) background control mice (C57BL/6) were subjected to bilateral renal artery clamping for 19 min and reperfusion for up to 6 weeks. Despite the acute protective effect of TLR4 inhibition on renal function (serum creatinine 1.6 ± 0.4 mg/dL TLR4-deletion vs. 2.8 ± 0.3 mg/dL·WT) and rates of tubular apoptosis following ischemic AKI, we found no difference in neutrophil or macrophage infiltration. Furthermore, we observed significant protection from microvascular rarefaction at six weeks following injury with TLR4-deletion, but this did not alter development of fibrosis. In conclusion, we validate the acute protective effect of TLR4 signal inhibition in AKI but demonstrate that this protective effect does not mitigate the sequential fibrogenic response in this model of ischemic AKI

Population density, water supply, and the risk of dengue fever in Vietnam: cohort study and spatial analysis.

BACKGROUND: Aedes aegypti, the major vector of dengue viruses, often breeds in water storage containers used by households without tap water supply, and occurs in high numbers even in dense urban areas. We analysed the interaction between human population density and lack of tap water as a cause of dengue fever outbreaks with the aim of identifying geographic areas at highest risk. METHODS AND FINDINGS: We conducted an individual-level cohort study in a population of 75,000 geo-referenced households in Vietnam over the course of two epidemics, on the basis of dengue hospital admissions (n = 3,013). We applied space-time scan statistics and mathematical models to confirm the findings. We identified a surprisingly narrow range of critical human population densities between around 3,000 to 7,000 people/km² prone to dengue outbreaks. In the study area, this population density was typical of villages and some peri-urban areas. Scan statistics showed that areas with a high population density or adequate water supply did not experience severe outbreaks. The risk of dengue was higher in rural than in urban areas, largely explained by lack of piped water supply, and in human population densities more often falling within the critical range. Mathematical modeling suggests that simple assumptions regarding area-level vector/host ratios may explain the occurrence of outbreaks. CONCLUSIONS: Rural areas may contribute at least as much to the dissemination of dengue fever as cities. Improving water supply and vector control in areas with a human population density critical for dengue transmission could increase the efficiency of control efforts. Please see later in the article for the Editors' Summary

Modeling the risk of malaria for travelers to areas with stable malaria transmission

BACKGROUND: Malaria is an important threat to travelers visiting endemic regions. The risk of acquiring malaria is complex and a number of factors including transmission intensity, duration of exposure, season of the year and use of chemoprophylaxis have to be taken into account estimating risk. MATERIALS AND METHODS: A mathematical model was developed to estimate the risk of non-immune individual acquiring falciparum malaria when traveling to the Amazon region of Brazil. The risk of malaria infection to travelers was calculated as a function of duration of exposure and season of arrival. RESULTS: The results suggest significant variation of risk for non-immune travelers depending on arrival season, duration of the visit and transmission intensity. The calculated risk for visitors staying longer than 4 months during peak transmission was 0.5% per visit. CONCLUSIONS: Risk estimates based on mathematical modeling based on accurate data can be a valuable tool in assessing risk/benefits and cost/benefits when deciding on the value of interventions for travelers to malaria endemic regions