[Predictors of Utilization of Cardiovascular and Respiratory Emergency Department Visits - what Impact does the Environment have?] / Prädiktoren der Inanspruchnahme von kardiovaskulären und respiratorischen Notfallaufnahmen ­ welchen Einfluss hat die Umwelt?

AIM: There has been an increasing number of emergency department (ED) visits recently. It is unclear whether, in addition to a shift in services from the outpatient to the inpatient sector, other causes, (e. g. environmental factors), play a role. The aim was to investigate associations between the number of cardiovascular and respiratory ED visits and environmental variables. METHODS: Highly correlated environmental data were subjected to a principal component analysis. By using cross-correlation functions, environmental variables with time lags that showed the highest correlation with the number of ED visits were taken into consideration in the UNIANOVA analysis model, together with, among others, the day of the week and interaction terms. RESULTS: The final regression model explained 47% of the variation in respiratory ED visits demonstrating main effects for Mondays (B=10.69; p<0.001). Season showed significant effects with highest ED visits in autumn. No direct associations between environmental variables and number of respiratory ED visits were found. The results for the cardiovascular outcome were less expressive (R2=0.20). Again, the day of the week had the main effect on cardiovascular ED visits (p<0.001). CONCLUSIONS: The results suggest that weekdays had the main effect on ED visits. In future, we will collect and analyze environmental data at the micro level to achieve a higher model quality and better interpretability.

Temporal analysis of determinants for respiratory emergency department visits in a large German hospital.

INTRODUCTION: Associations between air pollutants, meteorological conditions and respiratory diseases have been extensively shown. The aim of this study was to investigate associations between daily meteorological data, data on air pollution and emergency department (ED) visits depending on the day of the week, season and year (study period from 2013 to 2015). METHODS: Highly correlated environmental data entered a categorical principal components analysis (CATPCA). We analysed cross-correlation functions between the time series of the respective daily environmental factors and daily ED visits. Time lags with peak correlations of environmental variables obtained by the CATPCA on ED visits together with day of the week, year, running day (linear, quadratic and cubic), season and interaction terms entered the univariate analysis of variance (UNIANOVA) model. RESULTS: The analyses demonstrated main effects on ED visits for the day of the week with highest admission rates on Mondays (B=10.69; ƞ2=0.333; p<0.001). A significant time trend could be observed showing increasing numbers of ED visits per each year (p<0.001). The variable 'running day' (linear, quadratic and cubic) indicated a significant non-linear effect over time. The variable season showed significant results with winter, spring and summer recording fewer ED visits compared with the reference season autumn. Environmental variables showed no direct associations with respiratory ED visits. DISCUSSION: ED visits were significantly associated with temporal variables. Our data did not show direct associations between environmental variables and ED visits.In times of rapid urbanisation, increases in respiratory diseases, temperature and air pollution, our analyses can help focus future studies and enhance strategies to reduce increasing numbers of respiratory diseases and ED visits. Because the potential costs of medical care in hospitals can be high compared with physicians, public health recommendations for reducing the increasing ED visits should be promoted and evaluated.

Geographically weighted regression of land cover determinants of Plasmodium falciparum transmission in the Ashanti Region of Ghana.

BACKGROUND: Malaria is a mosquito-borne parasitic disease that causes severe mortality and morbidity, particularly in Sub-Saharan Africa. As the vectors predominantly bite between dusk and dawn, risk of infection is determined by the abundance of P. falciparum infected mosquitoes in the surroundings of the households. Remote sensing is commonly employed to detect associations between land use/land cover (LULC) and mosquito-borne diseases. Due to challenges in LULC identification and the fact that LULC merely functions as a proxy for mosquito abundance, assuming spatially homogenous relationships may lead to overgeneralized conclusions. METHODS: Data on incidence of P. falciparum parasitaemia were recorded by active and passive follow-up over two years. Nine LULC types were identified through remote sensing and ground-truthing. Spatial associations of LULC and P. falciparum parasitaemia rate were described in a semi-parametric geographically weighted Poisson regression model. RESULTS: Complete data were available for 878 individuals, with an annual P. falciparum rate of 3.2 infections per person-year at risk. The influences of built-up areas (median incidence rate ratio (IRR): 0.94, IQR: 0.46), forest (median IRR: 0.9, IQR: 0.51), swampy areas (median IRR: 1.15, IQR: 0.88), as well as banana (median IRR: 1.02, IQR: 0.25), cacao (median IRR: 1.33, IQR: 0.97) and orange plantations (median IRR: 1.11, IQR: 0.68) on P. falciparum rate show strong spatial variations within the study area. Incorporating spatial variability of LULC variables increased model performance compared to the spatially homogenous model. CONCLUSIONS: The observed spatial variability of LULC influence in parasitaemia would have been masked by traditional Poisson regression analysis assuming a spatially constant influence of all variables. We conclude that the spatially varying effects of LULC on P. falciparum parasitaemia may in fact be associated with co-factors not captured by remote sensing, and suggest that future studies assess small-scale spatial variation of vegetation to circumvent generalised assumptions on ecological associations that may in fact be artificial.

Seroprevalence of antibodies against Chikungunya, Dengue, and Rift Valley fever viruses after febrile illness outbreak, Madagascar.

In October 2009, two-3 months after an outbreak of a febrile disease with joint pain on the eastern coast of Madagascar, we assessed serologic markers for chikungunya virus (CHIKV), dengue virus (DENV), and Rift Valley fever virus (RVFV) in 1,244 pregnant women at 6 locations. In 2 eastern coast towns, IgG seroprevalence against CHIKV was 45% and 23%; IgM seroprevalence was 28% and 5%. IgG seroprevalence against DENV was 17% and 11%. No anti-DENV IgM was detected. At 4 locations, 450-1,300 m high, IgG seroprevalence against CHIKV was 0%-3%, suggesting CHIKV had not spread to higher inland-altitudes. Four women had IgG against RVFV, probably antibodies from a 2008 epidemic. Most (78%) women from coastal locations with CHIKV-specific IgG reported joint pain and stiffness; 21% reported no symptoms. CHIKV infection was significantly associated with high bodyweight. The outbreak was an isolated CHIKV epidemic without relevant DENV co-transmission.

Incidence and characteristics of bacteremia among children in rural Ghana.

The objective of the study was to describe systemic bacterial infections occurring in acutely ill and hospitalized children in a rural region in Ghana, regarding frequency, incidence, antimicrobial susceptibility patterns and associations with anthropometrical data.Blood cultures were performed in all children below the age of five years, who were admitted to Agogo Presbyterian Hospital (APH), Asante Region, Ghana, between September 2007 and July 2009. Medical history and anthropometrical data were assessed using a standardized questionnaire at admission. Incidences were calculated after considering the coverage population adjusted for village-dependent health-seeking behavior.Among 1,196 hospitalized children, 19.9% (n = 238) were blood culture positive. The four most frequent isolated pathogens were nontyphoidal salmonellae (NTS) (53.3%; n = 129), Staphylococcus aureus (13.2%; n = 32), Streptococcus pneumoniae (9.1%; n = 22) and Salmonella ser. Typhi (7.0%; n = 17). Yearly cumulative incidence of bacteremia was 46.6 cases/1,000 (CI 40.9-52.2). Yearly cumulative incidences per 1,000 of the four most frequent isolates were 25.2 (CI 21.1-29.4) for NTS, 6.3 (CI 4.1-8.4) for S. aureus, 4.3 (CI 2.5-6.1) for S. pneumoniae and 3.3 (CI 1.8-4.9) for Salmonella ser. Typhi. Wasting was positively associated with bacteremia and systemic NTS bloodstream infection. Children older than three months had more often NTS bacteremia than younger children. Ninety-eight percent of NTS and 100% of Salmonella ser. Typhi isolates were susceptible to ciprofloxacin, whereas both tested 100% susceptible to ceftriaxone. Seventy-seven percent of NTS and 65% of Salmonella ser. Typhi isolates were multi-drug resistant (MDR). Systemic bacterial infections in nearly 20% of hospitalized children underline the need for microbiological diagnostics, to guide targeted antimicrobial treatment and prevention of bacteremia. If microbiological diagnostics are lacking, calculated antimicrobial treatment of severely ill children in malaria-endemic areas should be considered.

Spatial analysis of land cover determinants of malaria incidence in the Ashanti Region, Ghana.

Malaria belongs to the infectious diseases with the highest morbidity and mortality worldwide. As a vector-borne disease malaria distribution is strongly influenced by environmental factors. The aim of this study was to investigate the association between malaria risk and different land cover classes by using high-resolution multispectral Ikonos images and Poisson regression analyses. The association of malaria incidence with land cover around 12 villages in the Ashanti Region, Ghana, was assessed in 1,988 children <15 years of age. The median malaria incidence was 85.7 per 1,000 inhabitants and year (range 28.4-272.7). Swampy areas and banana/plantain production in the proximity of villages were strong predictors of a high malaria incidence. An increase of 10% of swampy area coverage in the 2 km radius around a village led to a 43% higher incidence (relative risk [RR] = 1.43, p<0.001). Each 10% increase of area with banana/plantain production around a village tripled the risk for malaria (RR = 3.25, p<0.001). An increase in forested area of 10% was associated with a 47% decrease of malaria incidence (RR = 0.53, p = 0.029). Distinct cultivation in the proximity of homesteads was associated with childhood malaria in a rural area in Ghana. The analyses demonstrate the usefulness of satellite images for the prediction of malaria endemicity. Thus, planning and monitoring of malaria control measures should be assisted by models based on geographic information systems.

Modeling the relationship between precipitation and malaria incidence in children from a holoendemic area in Ghana.

Climatic factors influence the incidence of vector-borne diseases such as malaria. They modify the abundance of mosquito populations, the length of the extrinsic parasite cycle in the mosquito, the malarial dynamics, and the emergence of epidemics in areas of low endemicity. The objective of this study was to investigate temporal associations between weekly malaria incidence in 1,993 children < 15 years of age and weekly rainfall. A time series analysis was conducted by using cross-correlation function and autoregressive modeling. The regression model showed that the level of rainfall predicted the malaria incidence after a time lag of 9 weeks (mean = 60 days) and after a time lag between one and two weeks. The analyses provide evidence that high-resolution precipitation data can directly predict malaria incidence in a highly endemic area. Such models might enable the development of early warning systems and support intervention measures.

Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana.

BACKGROUND: The socioeconomic and sociodemographic situation are important components for the design and assessment of malaria control measures. In malaria endemic areas, however, valid classification of socioeconomic factors is difficult due to the lack of standardized tax and income data. The objective of this study was to quantify household socioeconomic levels using principal component analyses (PCA) to a set of indicator variables and to use a classification scheme for the multivariate analysis of children<15 years of age presented with and without malaria to an outpatient department of a rural hospital. METHODS: In total, 1,496 children presenting to the hospital were examined for malaria parasites and interviewed with a standardized questionnaire. The information of eleven indicators of the family's housing situation was reduced by PCA to a socioeconomic score, which was then classified into three socioeconomic status (poor, average and rich). Their influence on the malaria occurrence was analysed together with malaria risk co-factors, such as sex, parent's educational and ethnic background, number of children living in a household, applied malaria protection measures, place of residence and age of the child and the mother. RESULTS: The multivariate regression analysis demonstrated that the proportion of children with malaria decreased with increasing socioeconomic status as classified by PCA (p<0.05). Other independent factors for malaria risk were the use of malaria protection measures (p<0.05), the place of residence (p<0.05), and the age of the child (p<0.05). CONCLUSIONS: The socioeconomic situation is significantly associated with malaria even in holoendemic rural areas where economic differences are not much pronounced. Valid classification of the socioeconomic level is crucial to be considered as confounder in intervention trials and in the planning of malaria control measures.