Does donating blood for the first time during a national emergency create a better commitment to donating again?

BACKGROUND AND OBJECTIVES: Emergency situations often elicit a generous response from the public. This occurred after attacks on the US on September 11, 2001 when many new blood donors lined up to donate. This study was performed to compare return rates for first time donors (FTD) after September 11th, 2001 to FTD during a comparable period in 2000. MATERIALS AND METHODS: A total of 3315 allogeneic whole blood donations from FTD at a regional blood centre were collected between September 11th and 30th, 2001. Subsequent donations by the FTD before March 31, 2002 were reviewed. This (test) group was compared to 1279 FTD (control group) donating during the same time period in September 2000 and to their return rate in the subsequent 6 months. RESULTS: Following September 11, 2001, 1087/3315 (32.8%) FTD returned by March 31, 2002. This return rate was similar to the control group [427/1279 (33.4%)]. The deferral rate during the donor screening process for the control group was significantly higher than the deferral rate for the September 11-30, 2001 group (P < 0.01). The odds of an individual FTD returning increased with age, and the chance of a female donor returning was 1.13 times higher than a male (P = 0.06). There was a carryover effect after September 11, 2001 too. CONCLUSION: A national emergency, September 11, 2001, inspired people to donate blood for the first time. However, the proportion of return donations amongst them was not increased. Females and males in certain age groups were more likely to become repeat donors due to the residual effect of September 11, 2001. Additional efforts are needed to retain eligible FTD in donor pools.

Immigration to the USA and risk for mood and anxiety disorders: variation by origin and age at immigration.

BACKGROUND: Risk for mood and anxiety disorders associated with US-nativity may vary across immigrant groups. METHOD: Using data from the National Epidemiological Study of Alcohol and Related Conditions (NESARC), we examined the association of lifetime risk for mood and anxiety disorders with US-nativity and age at immigration across seven subgroups of the US population defined by country or region of ancestral origin: Mexico, Puerto-Rico, Cuba, Central and South America, Western Europe, Eastern Europe, and Africa and the Caribbean. Discrete time survival models were used to compare lifetime risk between the US-born, immigrants who arrived in the USA prior to the age of 13 years and immigrants who arrived in the USA at the age of 13 years or older. RESULTS: The association of risk for mood and anxiety disorders with US-nativity varies significantly across ancestral origin groups (p<0.001). Among people from Mexico, Eastern Europe, and Africa or the Caribbean, risk for disorders is lower relative to the US-born among immigrants who arrived at the age of 13 years or higher (odds ratios in the range 0.34-0.49) but not among immigrants who arrived prior to the age of 13 years. There is no association between US-nativity and risk for disorder among people from Western Europe and Puerto Rico. CONCLUSIONS: Low risk among immigrants relative to the US-born is limited to groups among whom risk for mood and anxiety disorder is low in immigrants who spent their pre-adolescent years outside of the USA.

Comparison of Models Analyzing a Small Number of Observed Meningitis Cases in Navrongo, Ghana.

The "meningitis belt" is a region in sub-Saharan Africa where annual outbreaks of meningitis occur, with epidemics observed cyclically. While we know that meningitis is heavily dependent on seasonal trends, the exact pathways for contracting the disease are not fully understood and warrant further investigation. Most previous approaches have used large sample inference to assess impacts of weather on meningitis rates. However, in the case of rare events, the validity of such assumptions is uncertain. This work examines the meningitis trends in the context of rare events, with the specific objective of quantifying the underlying seasonal patterns in meningitis rates. We compare three main classes of models: the Poisson generalized linear model, the Poisson generalized additive model, and a Bayesian hazard model extended to accommodate count data and a changing at-risk population. We compare the accuracy and robustness of the models through the bias, RMSE, and standard deviation of the estimators, and also provide a detailed case study of meningitis patterns for data collected in Navrongo, Ghana.