Linking influenza epidemic onsets to covariates at different scales using a dynamical model.

BACKGROUND: Evaluating the factors favoring the onset of influenza epidemics is a critical public health issue for surveillance, prevention and control. While past outbreaks provide important insights for understanding epidemic onsets, their statistical analysis is challenging since the impact of a factor can be viewed at different scales. Indeed, the same factor can explain why epidemics are more likely to begin (i) during particular weeks of the year (global scale); (ii) earlier in particular regions (spatial scale) or years (annual scale) than others and (iii) earlier in some years than others within a region (spatiotemporal scale). METHODS: Here, we present a statistical approach based on dynamical modeling of infectious diseases to study epidemic onsets. We propose a method to disentangle the role of covariates at different scales and use a permutation procedure to assess their significance. Epidemic data gathered from 18 French regions over six epidemic years were provided by the Regional Influenza Surveillance Group (GROG) sentinel network. RESULTS: Our results failed to highlight a significant impact of mobility flows on epidemic onset dates. Absolute humidity had a significant impact, but only at the spatial scale. No link between demographic covariates and influenza epidemic onset dates could be established. DISCUSSION: Dynamical modeling presents an interesting basis to analyze spatiotemporal variations in the outcome of epidemic onsets and how they are related to various types of covariates. The use of these models is quite complex however, due to their mathematical complexity. Furthermore, because they attempt to integrate migration processes of the virus, such models have to be much more explicit than pure statistical approaches. We discuss the relation of this approach to survival analysis, which present significant differences but may constitute an interesting alternative for non-methodologists.

Quantifying the role of weather on seasonal influenza.

BACKGROUND: Improving knowledge about influenza transmission is crucial to upgrade surveillance network and to develop accurate predicting models to enhance public health intervention strategies. Epidemics usually occur in winter in temperate countries and during the rainy season for tropical countries, suggesting a climate impact on influenza spread. Despite a lot of studies, the role of weather on influenza spread is not yet fully understood. In the present study, we investigated this issue at two different levels. METHODS: First, we evaluated how weekly (intra-annual) incidence variations of clinical diseases could be linked to those of climatic factors. We considered that only a fraction of the human population is susceptible at the beginning of a year due to immunity acquired from previous years. Second, we focused on epidemic sizes (cumulated number of clinical reported cases) and looked at how their inter-annual and regional variations could be related to differences in the winter climatic conditions of the epidemic years over the regions. We quantified the impact of fifteen climatic variables in France using the Réseau des GROG surveillance network incidence data over eleven regions and nine years. RESULTS: At the epidemic scale, no impact of climatic factors was highlighted. At the intra-annual scale, six climatic variables had a significant impact: average temperature (5.54 ± 1.09 %), absolute humidity (5.94 ± 1.08 %), daily variation of absolute humidity (3.02 ± 1.17 %), sunshine duration (3.46 ± 1.06 %), relative humidity (4.92 ± 1.20 %) and daily variation of relative humidity (4.46 ± 1.24 %). Since in practice the impact of two highly correlated variables is very hard to disentangle, we performed a principal component analysis that revealed two groups of three highly correlated climatic variables: one including the first three highlighted climatic variables on the one hand, the other including the last three ones on the other hand. CONCLUSIONS: These results suggest that, among the six factors that appeared to be significant, only two (one per group) could in fact have a real effect on influenza spread, although it is not possible to determine which one based on a purely statistical argument. Our results support the idea of an important role of climate on the spread of influenza.

Trapping the Tiger: Efficacy of the Novel BG-Sentinel 2 With Several Attractants and Carbon Dioxide for Collecting Aedes albopictus (Diptera: Culicidae) in Southern France.

Targeted trapping of mosquito disease vectors plays an important role in the surveillance and control of mosquito-borne diseases. The Asian tiger mosquito, Aedes albopictus (Skuse), is an invasive species, which is spreading throughout the world, and is a potential vector of 24 arboviruses, particularly efficient in the transmission of chikungunya, dengue, and zika viruses. Using a 4 × 4 Latin square design, we assessed the efficacy of the new BG-Sentinel 2 mosquito trap using the attractants BG-lure and (R)-1-octen-3-ol cartridge, alone or in combination, and with and without carbon dioxide, for the field collection of Ae. albopictus mosquitoes.We found a synergistic effect of attractant and carbon dioxide that significantly increased twofold to fivefold the capture rate of Ae. albopictus. In combination with carbon dioxide, BG-lure cartridge is more effective than (R)-1-octen-3-ol in attracting females, while a combination of both attractants and carbon dioxide is the most effective for capturing males. In the absence of carbon dioxide, BG-lure cartridge alone did not increase the capture of males or females when compared with an unbaited trap. However, the synergistic effect of carbon dioxide and BG-lure makes this the most efficient combination in attracting Ae. albopictus.

Modes of transmission of Simian T-lymphotropic Virus Type 1 in semi-captive mandrills (Mandrillus sphinx).

Non-human primates (NHPs) often live in inaccessible areas, have cryptic behaviors, and are difficult to follow in the wild. Here, we present a study on the spread of the simian T-lymphotropic Virus Type 1 (STLV-1), the simian counterpart of the human T-lymphotropic virus type 1 (HTLV-1) in a semi-captive mandrill colony. This study combines 28 years of longitudinal monitoring, including behavioral data, with a dynamic mathematical model and Bayesian inference. Three transmission modes were suspected: aggressive, sexual and familial. Our results show that among males, STLV-1 transmission occurs preferentially via aggression. Because of their impressive aggressive behavior male mandrills can easily transmit the virus during fights. On the contrary, sexual activity seems to have little effect. Thus transmission appears to occur primarily via male-male and female-female contact. In addition, for young mandrills, familial transmission appears to play an important role in virus spread.

Quantifying transmission by stage of infection in the field: the example of SIV-1 and STLV-1 infecting mandrills.

The early stage of viral infection is often followed by an important increase of viral load and is generally considered to be the most at risk for pathogen transmission. Most methods quantifying the relative importance of the different stages of infection were developed for studies aimed at measuring HIV transmission in Humans. However, they cannot be transposed to animal populations in which less information is available. Here we propose a general method to quantify the importance of the early and late stages of the infection on micro-organism transmission from field studies. The method is based on a state space dynamical model parameterized using Bayesian inference. It is illustrated by a 28 years dataset in mandrills infected by Simian Immunodeficiency Virus type-1 (SIV-1) and the Simian T-Cell Lymphotropic Virus type-1 (STLV-1). For both viruses we show that transmission is predominant during the early stage of the infection (transmission ratio for SIV-1: 1.16 [0.0009; 18.15] and 9.92 [0.03; 83.8] for STLV-1). However, in terms of basic reproductive number (R0 ), which quantifies the weight of both stages in the spread of the virus, the results suggest that the epidemics of SIV-1 and STLV-1 are mainly driven by late transmissions in this population.

Efficacy of mosquito traps for collecting potential West Nile mosquito vectors in a natural Mediterranean wetland.

Surveillance, research, and control of mosquito-borne diseases such as West Nile virus require efficient methods for sampling mosquitoes. We compared the efficacy of BG-Sentinel and Centers for Disease Control and Prevention (CDC)-CO(2) traps in terms of the abundances of host-seeking and blood-fed female mosquitoes and the origin of mosquito bloodmeals. Our results indicate that BG-Sentinel traps that use CO(2) and attractants are as effective as CDC-CO(2) traps for Culex mosquito species, Ochlerotatus caspius, and they are also highly efficient at capturing Anopheles atroparvus host-seeking and blood-fed females with or without CO(2). The CDC-CO(2) trap is the least efficient method for capturing blood-fed females. BG-Sentinel traps with attractants and CO(2) were significantly better at capturing mosquitoes that had fed on mammals than the unbaited BG-Sentinel and CDC-CO(2) traps in the cases of An. atroparvus and Cx. theileri. These results may help researchers to optimize trapping methods by obtaining greater sample sizes and saving time and money.