The unexpected importance of mosquito oviposition behaviour for malaria: non-productive larval habitats can be sources for malaria transmission

BACKGROUND: Mosquitoes commute between blood-meal hosts and water. Thus, heterogeneity in human biting reflects underlying spatial heterogeneity in the distribution and suitability of larval habitat as well as inherent differences in the attractiveness, suitability and distribution of blood-meal hosts. One of the possible strategies of malaria control is to identify local vector species and then attack water bodies that contain their larvae. METHODS: Biting and host seeking, not oviposition, have been the focus of most previous studies of mosquitoes and malaria transmission. This study presents a mathematical model that incorporates mosquito oviposition behaviour. RESULTS: The model demonstrates that oviposition is one potential factor explaining heterogeneous biting and vector distribution in a landscape with a heterogeneous distribution of larval habitat. Adult female mosquitoes tend to aggregate around places where they oviposit, thereby increasing the risk of malaria, regardless of the suitability of the habitat for larval development. Thus, a water body may be unsuitable for adult mosquito emergence, but simultaneously, be a source for human malaria. CONCLUSION: Larval density may be a misleading indicator of a habitat's importance for malaria control. Even if mosquitoes could be lured to oviposit in sprayed larval habitats, this would not necessarily mitigate – and might aggravate – the risk of malaria transmission. Forcing mosquitoes to fly away from humans in search of larval habitat may be a more efficient way to reduce the risk of malaria than killing larvae. Thus, draining, fouling, or filling standing water where mosquitoes oviposit can be more effective than applying larvicide

Comparative evaluation by semiquantitative reverse transcriptase polymerase chain reaction of MDR1, MRP and GSTp gene expression in breast carcinomas.

Identification and quantitative evaluation of drug resistance markers are essential to assess the impact of multidrug resistance (MDR) in clinical oncology. The MDR1 gene confers pleiotropic drug resistance in tumour cells, but other molecular mechanisms are also involved in drug resistance. In particular, the clinical pattern of expression of the other MDR-related genes is unclear and their interrelationships are still unknown. Here, we report standardization of the procedures used to determine a reliable method of semiquantitative reverse transcriptase polymerase chain reaction (RT-PCR) using a standard series of drug-sensitive and increasingly resistant cell lines to evaluate the expression of three MDR-related genes, i.e. MDR1 (multidrug resistance gene 1), MRP (multidrug resistance related protein) and GSTp (glutathione-S-transferase p), reported to be endogenous standard genes for normalization of mRNAs. A total of 74 breast cancer surgical biopsies, obtained before any treatment, were evaluated by this method. When compared with classical clinical and laboratory findings, GSTp mRNA level was higher in diploid tumours. However, the main finding of our study suggests a clear relationship between two of these MDR-related gene expressions, namely GSTp and MRP. This finding provides new insight into human breast tumours, which may possibly be linked to the glutathione conjugate carrier function of MRP. Well defined semiquantitative RT-PCR procedures can therefore constitute a powerful tool to investigate MDR phenotype at mRNA levels of different related genes in small and precious tumour biopsy specimens

The Geographic Synchrony of Seasonal Influenza: A Waves across Canada and the United States

BACKGROUND: As observed during the 2009 pandemic, a novel influenza virus can spread globally before the epidemic peaks locally. As consistencies in the relative timing and direction of spread could form the basis for an early alert system, the objectives of this study were to use the case-based reporting system for laboratory confirmed influenza from the Canadian FluWatch surveillance program to identify the geographic scale at which spatial synchrony exists and then to describe the geographic patterns of influenza A virus across Canada and in relationship to activity in the United States (US). METHODOLOGY/PRINCIPAL FINDINGS: Weekly laboratory confirmations for influenza A were obtained from the Canadian FluWatch and the US FluView surveillance programs from 1997/98 to 2006/07. For the six seasons where at least 80% of the specimens were antigenically similar, we identified the epidemic midpoint of the local/regional/provincial epidemics and analyzed trends in the direction of spread. In three out of the six seasons, the epidemic appeared first in Canada. Regional epidemics were more closely synchronized across the US (3-5 weeks) compared to Canada (5-13 weeks), with a slight gradient in timing from the southwest regions in the US to northeast regions of Canada and the US. Cities, as well as rural areas within provinces, usually peaked within a couple of weeks of each other. The anticipated delay in peak activity between large cities and rural areas was not observed. In some mixed influenza A seasons, lack of synchronization sub-provincially was evident. CONCLUSIONS/SIGNIFICANCE: As mixing between regions appears to be too weak to force a consistency in the direction and timing of spread, local laboratory-based surveillance is needed to accurately assess the level of influenza activity in the community. In comparison, mixing between urban communities and adjacent rural areas, and between some communities, may be sufficient to force synchronization

Medication Sales and Syndromic Surveillance, France

Real-time over-the-counter drug sales provide an additional tool for disease surveillance

Does the Effectiveness of Control Measures Depend on the Influenza Pandemic Profile?

BACKGROUND: Although strategies to contain influenza pandemics are well studied, the characterization and the implications of different geographical and temporal diffusion patterns of the pandemic have been given less attention. METHODOLOGY/MAIN FINDINGS: Using a well-documented metapopulation model incorporating air travel between 52 major world cities, we identified potential influenza pandemic diffusion profiles and examined how the impact of interventions might be affected by this heterogeneity. Clustering methods applied to a set of pandemic simulations, characterized by seven parameters related to the conditions of emergence that were varied following Latin hypercube sampling, were used to identify six pandemic profiles exhibiting different characteristics notably in terms of global burden (from 415 to >160 million of cases) and duration (from 26 to 360 days). A multivariate sensitivity analysis showed that the transmission rate and proportion of susceptibles have a strong impact on the pandemic diffusion. The correlation between interventions and pandemic outcomes were analyzed for two specific profiles: a fast, massive pandemic and a slow building, long-lasting one. In both cases, the date of introduction for five control measures (masks, isolation, prophylactic or therapeutic use of antivirals, vaccination) correlated strongly with pandemic outcomes. Conversely, the coverage and efficacy of these interventions only moderately correlated with pandemic outcomes in the case of a massive pandemic. Pre-pandemic vaccination influenced pandemic outcomes in both profiles, while travel restriction was the only measure without any measurable effect in either. CONCLUSIONS: our study highlights: (i) the great heterogeneity in possible profiles of a future influenza pandemic; (ii) the value of being well prepared in every country since a pandemic may have heavy consequences wherever and whenever it starts; (iii) the need to quickly implement control measures and even to anticipate pandemic emergence through pre-pandemic vaccination; and (iv) the value of combining all available control measures except perhaps travel restrictions

Predicting Pneumonia and Influenza Mortality from Morbidity Data

BACKGROUND: Few European countries conduct reactive surveillance of influenza mortality, whereas most monitor morbidity. METHODOLOGY/PRINCIPAL FINDINGS: We developed a simple model based on Poisson seasonal regression to predict excess cases of pneumonia and influenza mortality during influenza epidemics, based on influenza morbidity data and the dominant types/subtypes of circulating viruses. Epidemics were classified in three levels of mortality burden (“high”, “moderate” and “low”). The model was fitted on 14 influenza seasons and was validated on six subsequent influenza seasons. Five out of the six seasons in the validation set were correctly classified. The average absolute difference between observed and predicted mortality was 2.8 per 100,000 (18% of the average excess mortality) and Spearman's rank correlation coefficient was 0.89 (P = 0.05). CONCLUSIONS/SIGNIFICANCE: The method described here can be used to estimate the influenza mortality burden in countries where specific pneumonia and influenza mortality surveillance data are not available

Social sciences research in neglected tropical diseases 2: A bibliographic analysis

The official published version of the article can be found at the link below.Background There are strong arguments for social science and interdisciplinary research in the neglected tropical diseases. These diseases represent a rich and dynamic interplay between vector, host, and pathogen which occurs within social, physical and biological contexts. The overwhelming sense, however, is that neglected tropical diseases research is a biomedical endeavour largely excluding the social sciences. The purpose of this review is to provide a baseline for discussing the quantum and nature of the science that is being conducted, and the extent to which the social sciences are a part of that. Methods A bibliographic analysis was conducted of neglected tropical diseases related research papers published over the past 10 years in biomedical and social sciences. The analysis had textual and bibliometric facets, and focussed on chikungunya, dengue, visceral leishmaniasis, and onchocerciasis. Results There is substantial variation in the number of publications associated with each disease. The proportion of the research that is social science based appears remarkably consistent (<4%). A textual analysis, however, reveals a degree of misclassification by the abstracting service where a surprising proportion of the "social sciences" research was pure clinical research. Much of the social sciences research also tends to be "hand maiden" research focused on the implementation of biomedical solutions. Conclusion There is little evidence that scientists pay any attention to the complex social, cultural, biological, and environmental dynamic involved in human pathogenesis. There is little investigator driven social science and a poor presence of interdisciplinary science. The research needs more sophisticated funders and priority setters who are not beguiled by uncritical biomedical promises