The impact of flooding on residential property values in England

Severe flooding throughout England in Autumn 1998 and 2000, has seen an increase in the extent of flood liable residential areas throughout England, as well as an increase in the actual levels of flood damage in all previously recognised flood prone residential areas. The increasing cost of rectifying the damage caused to residential properties from flooding has been of some concern to the residential property valuation profession and sales and leasing agency practices. However, the increasing trend in the frequency of flooding in England, combined with an increase in severity of flooding is now causing some degree of concern in the residential insurance and housing finance sectors. In order to determine and quantify the impact of flooding and flood damage on the residential property market in England, a survey of Chartered Surveyors and Chartered Real Estate Valuers has been carried out across the main flood affected counties of England. This survey will provide similar details to the research completed by Eves (1999, 2001) and Fibbens (1993) in relation to residential property flooding in Australia. This survey provides comprehensive responses in relation to the degree of flood affectation across counties, the effect of flooding on residential property values, the impact of flooding on building insurance premiums and possible difficulties in obtaining finance to purchase residential property in recognised flood areas.

Modélisation de l'espérance de vie des clients en assurance

Dans ce mémoire, nous proposons une méthodologie statistique permettant d’obtenir un estimateur de l’espérance de vie des clients en assurance. Les prédictions effectuées tiennent compte des caractéristiques individuelles des clients, notamment du fait qu’ils peuvent détenir différents types de produits d’assurance (automobile, résidentielle ou les deux). Trois approches sont comparées. La première approche est le modèle de Markov simple, qui suppose à la fois l’homogénéité et la stationnarité des probabilités de transition. L’autre modèle – qui a été implémenté par deux approches, soit une approche directe et une approche par simulations – tient compte de l’hétérogénéité des probabilités de transition, ce qui permet d’effectuer des prédictions qui évoluent avec les caractéristiques des individus dans le temps. Les probabilités de transition de ce modèle sont estimées par des régressions logistiques multinomiales.

Section 232 mortgage insurance for residential care facilities (nursing homes, intermediate care facilities, and board and care homes.

"Replaces HUD handbook 4600.1 dated July, 1973."

Accounting for risk: The advent of capped conveyancing title insurance

Title insurance companies originating from America, have, in the past 15 years become part of the Australian conveyancing landscape. However for most residential freehold owners, their activities would be a mystery. A purchaser does not routinely obtain title insurance, with the companies presently focussing on servicing the mortgagee sector. While the lack of penetration in the residential purchaser market may be attributed to the consumer’s lack of knowledge, evidence from Ontario and New Zealand illustrates that title insurance is likely to become an additional cost in the conveyancing process in Australia. In this article we highlight the reasons why, and demonstrate how title insurers have, by working with the legal profession been able to subtly move the risk of responsibility for compensation for loss, (at least in the first instance) from the state to the insurer, but with the added benefit for the state and the conveyancing agents that the cost of the insurance is ultimately borne by the consumer. In New Zealand this development is being accelerated by the introduction of capped conveyancing title insurance. Whether title insurance will become part of the conveyancing process is no longer the relevant question for Australia, (it undoubtedly will), but the unknown issue is just how title insurance companies will work with conveyancing agents to infiltrate the market, and what response this infiltration will have in terms of the state’s view as to their continued role in the provision of assurance. We suggest that developments from New Zealand in relation to capped conveyancing insurance are likely to be replicated in Australia in the near future, and that the state’s role in providing an assurance fund will continue, though the state may seek to expand the areas in which the right to compensation is restricted.

Which rural migrants receive social insurance in Chinese cities? Evidence from Jiangsu survey data

This article draws on a survey of internal migrant workers in China's Jiangsu province to shed light on the characteristics of migrant workers who receive social insurance and explain why some migrants take up social insurance while others do not. Of the factors which potentially explain which migrants receive social insurance, gender, past earnings, ties to the city to which the migrant had moved, the ownership type of the enterprise in which the migrant works and residential registration status are all found to be statistically significant predictors. The article concludes with the suggestion that the high level of scepticism with respect to social protection that has been reported as being manifest among migrants is justified. There is little likelihood the majority of migrant workers who have moved to China's towns and cities will be able to access the social insurance benefits traditionally available to those with urban registration. Copyright © 2005 SAGE Publications London.

The characterization of residential fungal spores and the relationship with housing characteristics in the Houston area

A number of indoor environmental factors, including bioaerosol or aeroallergen concentrations have been identified as exacerbators for asthma and allergenic conditions of the respiratory system. People generally spend 90% to 95% of their time indoors. Therefore, understanding the environmental factors that affect the presence of aeroallergens indoors as well as outdoors is important in determining their health impact, and in identifying potential intervention methods. This study aimed to assess the relationship between indoor airborne fungal spore concentrations and indoor surface mold levels, indoor versus outdoor airborne fungal spore concentrations and the effect of previous as well as current water intrusion. Also, the association between airborne concentration of indoor fungal spores and surface mold levels and the age of the housing structure were examined. Further, the correlation between indoor concentrations of certain species was determined as well. ^ Air and surface fungal measurements and related information were obtained from a Houston-area data set compiled from visits to homes filing insurance claims. During the sampling visit these complaint homes exhibited either visible mold or a combination of visible mold and water intrusion problems. These data were examined to assess the relationships between the independent and dependent variables using simple linear regression analysis, and independent t-tests. To examine the correlation between indoor concentrations of certain species, Spearman correlation coefficients were used. ^ There were 126 houses sampled, with spring, n=43 (34.1%), and winter, n=42 (33.3%), representing the seasons with the most samples. The summer sample illustrated the highest geometric mean concentration of fungal spores, GM=5,816.5 relative to winter, fall and spring (GM=1,743.4, GM=3,683.5 and GM=2,507.4, respectively). In all seasons, greater concentrations of fungal spores were observed during the cloudy weather conditions. ^ The results indicated no statistically significant association between outdoor total airborne fungal spore concentration and total living room airborne fungal spore concentration (β = 0.095, p = 0.491). Second, living room surface mold levels were not associated with living room airborne fungal spore concentration, (β= 0.011, p = 0.669). Third, houses with and without previous water intrusion did not differ significantly with respect to either living room (t(111) = 0.710, p = 0.528) or bedroom (t(111) =1.673, p = 0.162) airborne fungal spore concentrations. Likewise houses with and without current water intrusion did not differ significantly with respect to living room (t(109)=0.716, p = 0.476) or bedroom (t(109) = 1.035, p = 0.304) airborne fungal spore concentration. Fourth, houses with and without current water intrusion did not differ significantly with respect to living room (χ 2 (5) = 5.61, p = 0.346), or bedroom (χ 2 (5) = 1.80, p = 0.875) surface mold levels. Fifth, the age of the house structure did not predict living room (β = 0.023, p = 0.102) and bedroom (β = 0.023, p = 0.065) surface mold levels nor living room (β = 0.002, p = 0.131) and bedroom (β = 0.001, p = 0.650) fungal spore airborne concentration. Sixth, in houses with visually observed mold growth there was statistically significant differences between the mean living room concentrations and mean outdoor concentrations for Cladosporium (t (107) = 11.73, p < 0.0001), Stachybotrys (t (106)=2.288, p = 0.024, and Nigrosporia (t (102) = 2.267, p = 0.025). Finally, there was a significant correlation between several living room fungal species pairs, namely, Cladosporium and Stachybotrys (r = 0.373, p <0.01, n=65), Curvularia and Aspergillus/Penicillium (r = 0.205, p < 0.05, n= 111)), Curvularia and Stachybotrys (r = 0.205, p < 0.05, n=111), Nigrospora and Chaetomium (r = 0.254, p < 0.01, n=105) and Stachybotrys and Nigrospora (r = 0.269, p < 0.01, n=105). ^ This study has demonstrated several positive findings, i.e., significant pairwise correlations of concentrations of several fungal species in living room air, and significant differences between indoor and outdoor concentrations of three fungal species in homes with visible mold. No association was observed between indoor and outdoor fungal spore concentrations. Neither living room nor bedroom airborne spore concentrations and surface mold levels were related to the age of the house or to water intrusion, either previous or current. Therefore, these findings suggest the need for evaluating additional parameters, as well as combinations of factors such as humidity, temperature, age of structure, ventilation, and room size to better understand the determinants of airborne fungal spore concentrations and surface mold levels in homes. ^

A pilot study on the effect of indoor particle sources on indoor particle concentration in residential houses

Characterization of indoor particle sources from 14 residential houses in Brisbane, Australia, was performed. The approximation of PM2.5 and the submicrometre particle number concentrations were measured simultaneously for more than 48 h in the kitchen of all the houses by using a photometer (DustTrak) and a condensation particle counter (CPC), respectively. From the real time indoor particle concentration data and a diary of indoor activities, the indoor particle sources were identified. The study found that among the indoor activities recorded in this study, frying, grilling, stove use, toasting, cooking pizza, smoking, candle vaporizing eucalyptus oil and fan heater use, could elevate the indoor particle number concentration levels by more than five times. The indoor approximation of PM2.5 concentrations could be close to 90 times, 30 times and three times higher than the background levels during grilling, frying and smoking, respectively.

Indoor exposure to submicrometer particles and PM2.5 in residential houses in Brisbane, Australia

As part of a large study investigating indoor air in residential houses in Brisbane, Australia, the purpose of this work was to quantify indoor exposure to submicrometer particles and PM2.5 for the inhabitants of 14 houses. Particle concentrations were measured simultaneously for more than 48 hours in the kitchens of all the houses by using a condensation particle counter (CPC) and a photometer (DustTrak). The occupants of the houses were asked to fill in a diary, noting the time and duration of any activity occurring throughout the house during measurement, as well as their presence or absence from home. From the time series concentration data and the information about indoor activities, exposure to the inhabitants of the houses was calculated for the entire time they spent at home as well as during indoor activities resulting in particle generation. The results show that the highest median concentration level occurred during cooking periods for both particle number concentration (47.5´103 particles cm-3) and PM2.5 concentration (13.4 mg m-3). The highest residential exposure period was the sleeping period for both particle number exposure (31%) and PM2.5 exposure (45.6%). The percentage of the average residential particle exposure level in total 24h particle exposure level was approximating 70% for both particle number and PM2.5 exposure.