In tropical and subtropical regions of eastern and South-eastern Asia, dengue fever (DF) and dengue hemorrhagic fever (DHF) outbreaks occur frequently. Previous studies indicate an association between meteorological variables and dengue incidence using time series analyses. The impacts of meteorological changes can affect dengue outbreak. However, difficulties in collecting detailed time series data in developing countries have led to common use of monthly data in most previous studies. In addition, time series analyses are often limited to one area because of the difficulty in collecting meteorological and dengue incidence data in multiple areas. To gain better understanding, we examined the effects of meteorological factors on dengue incidence in three geographically distinct areas (Ratnapura, Colombo, and Anuradhapura) of Sri Lanka by time series analysis of weekly data. The weekly average maximum temperature and total rainfall and the total number of dengue cases from 2005 to 2011 (7 years) were used as time series data in this study. Subsequently, time series analyses were performed on the basis of ordinary least squares regression analysis followed by the vector autoregressive model (VAR). In conclusion, weekly average maximum temperatures and the weekly total rainfall did not significantly affect dengue incidence in three geographically different areas of Sri Lanka. However, the weekly total rainfall slightly influenced dengue incidence in the cities of Colombo and Anuradhapura.

BackgroundIdentification of malaria vector breeding sites can enhance control activities. Although associations between malaria vector breeding sites and topography are well recognized, practical models that predict breeding sites from topographic information are lacking. We used topographic variables derived from remotely sensed Digital Elevation Models (DEMs) to model the breeding sites of malaria vectors. We further compared the predictive strength of two different DEMs and evaluated the predictability of various habitat types inhabited by Anopheles larvae.MethodsUsing GIS techniques, topographic variables were extracted from two DEMs: 1) Shuttle Radar Topography Mission 3 (SRTM3, 90-m resolution) and 2) the Advanced Spaceborne Thermal Emission Reflection Radiometer Global DEM (ASTER, 30-m resolution). We used data on breeding sites from an extensive field survey conducted on an island in western Kenya in 2006. Topographic variables were extracted for 826 breeding sites and for 4520 negative points that were randomly assigned. Logistic regression modelling was applied to characterize topographic features of the malaria vector breeding sites and predict their locations. Model accuracy was evaluated using the area under the receiver operating characteristics curve (AUC).ResultsAll topographic variables derived from both DEMs were significantly correlated with breeding habitats except for the aspect of SRTM. The magnitude and direction of correlation for each variable were similar in the two DEMs. Multivariate models for SRTM and ASTER showed similar levels of fit indicated by Akaike information criterion (3959.3 and 3972.7, respectively), though the former was slightly better than the latter. The accuracy of prediction indicated by AUC was also similar in SRTM (0.758) and ASTER (0.755) in the training site. In the testing site, both SRTM and ASTER models showed higher AUC in the testing sites than in the training site (0.829 and 0.799, respectively). The predictability of habitat types varied. Drains, foot-prints, puddles and swamp habitat types were most predictable.ConclusionsBoth SRTM and ASTER models had similar predictive potentials, which were sufficiently accurate to predict vector habitats. The free availability of these DEMs suggests that topographic predictive models could be widely used by vector control managers in Africa to complement malaria control strategies.

The actual state of intestinal long-term colonization by extended-spectrum ␤-lactamase (ESBL)-producing Escherichia coli in healthy Japanese people remains unclear. Therefore, a total of 4,314 fecal samples were collected from 2,563 food handlers from January 2010 to December 2011. Approximately 0.1 g of each fecal sample was inoculated onto a MacConkey agar plate containing cefotaxime (1 g/ml). The bacterial colonies that grew on each plate were checked for ESBL production by the double-disk synergy test, as recommended by the Clinical and Laboratory Standards Institute. The bacterial serotype, antimicrobial susceptibility, pulsotype, sequence type (ST), and ESBL genotype were checked, and the replicon types of plasmids harboring the ESBL gene were also determined after conjugation experiments. ESBL producers were recovered from 70 (3.1%) of 2,230 participants who were checked only once. On the other hand, ESBL producers were isolated at least once from 52 (15.6%) of 333 participants who were checked more than twice, and 13 of the 52 participants carried ESBL producers for from more than 3 months to up to 2 years. Fluoroquinolone (FQ)-resistant E. coli strains harboring bla CTX-M were repeatedly recovered from 11 of the 13 carriers of bla CTX-M -harboring E. coli. A genetically related FQ-resistant E. coli O25b:H4-ST131 isolate harboring bla CTX-M-27 was recovered from 4 of the 13 carriers for more than 6 months. Three FQ-resistant E. coli O1:H6-ST648 isolates that harbored bla CTX-M-15 or bla CTX-M-14 were recovered from 3 carriers. Moreover, multiple CTX-M-14-or CTX-M-15-producing E. coli isolates with different serotypes were recovered from 2 respective carriers. These findings predict a provable further spread of ESBL producers in both community and clinical settings.

Contamination of retail meat with extended-spectrum β-lactamase (ESBL)-producing Escherichia coli has been reported, but only limited data have been documented in Japan. One hundred fifty-three retail foods including chicken meat, beef, pork, and vegetables were purchased from 29 supermarkets between January and October in 2010. ESBL producers were recovered from each food sample using McConkey agar plate supplemented with 1 mg/L of cefotaxime. ESBL type was identified by DNA sequencing analysis after polymerase chain reaction amplification. Antibiogram, O serotype, plasmid replicon type, pulsotype, and multilocus sequence type were also determined. Fifty-two epidemiologically unrelated Escherichia coli isolates producing ESBL were recovered from 35 (22.9%) of 153 samples, all of which were chicken meat. ESBL types were mainly CTX-M-2 group followed by CTX-M-1 group and CTX-M-8 group. The numbers of bacterial isolates (8 of 21, 38.1%) harboring bla(CTX-M-8) recovered from imported meat samples were significantly larger than those of domestic ones (one of 31, 3.2%) (p<0.05). Nine O serotypes (mainly O8, O25, and O1) were found, together with O-antigen untypable (OUT). Four E. coli belonging to the O25b:H4-ST131 clone were recovered from domestic (n=1) and imported meat samples (n=3), respectively. These four isolates were susceptible to fluoroquinolones, although the E. coli O25b:H4-ST131 clone producing CTX-M-15, which is predominant in human isolates, is usually resistant to fluoroquinolones. By contrast, five CTX-M-15-producing E. coli strains were recovered only from domestic meat samples, and their serotypes were O8 or OUT instead of predominant serotype O25b. Our results showed that ESBL-producing E. coli isolates recovered from retail chicken meat samples in Japan are generally divergent in both genetic and serological aspects. Further comparative analyses of bla(CTX-M)-mediating genetic elements would be continued in the next step to characterize the ESBL producers from retail foods in Japan.

BackgroundThe Health and Demographic Surveillance System (HDSS) is a longitudinal data collection process that systematically and continuously monitors population dynamics for a specified population in a geographically defined area that lacks an effective system for registering demographic information and vital events.MethodsHDSS programs have been run in 2 regions in Kenya: in Mbita district in Nyanza province and Kwale district in Coast Province. The 2 areas have different disease burdens and cultures. Vital events were obtained by using personal digital assistants and global positioning system devices. Additional health-related surveys have been conducted bimonthly using various PDA-assisted survey software.ResultsThe Mbita HDSS covers 55 929 individuals, and the Kwale HDSS covers 42 585 individuals. In the Mbita HDSS, the life expectancy was 61.0 years for females and 57.5 years for males. Under-5 mortality was 91.5 per 1000 live births, and infant mortality was 47.0 per 1000 live births. The total fertility rate was 3.7 per woman. Data from the Kwale HDSS were not available because it has been running for less than 1 year at the time of this report.ConclusionsOur HDSS programs are based on a computer-assisted survey system that provides a rapid and flexible data collection platform in areas that lack an effective basic resident registration system. Although the HDSS areas are not representative of the entire country, they provide a base for several epidemiologic and social study programs, and for practical community support programs that seek to improve the health of the people in these areas.