Choosing a Survey Sample When Data on the Population Are Limited: A Method Using Global Positioning Systems and Aerial and Satellite Photographs

Background Various methods have been proposed for sampling when data on the population are limited. However, these methods are often biased. We propose a new method to draw a population sample using Global Positioning Systems and aerial or satellite photographs. Results We randomly sampled Global Positioning System locations in designated areas. A circle was drawn around each location with radius representing 20 m. Buildings in the circle were identified from satellite photographs; one was randomly chosen. Interviewers selected one household from the building, and interviews were conducted with eligible household members. Conclusions Participants had known selection probabilities, allowing proper estimation of parameters of interest and their variances. The approach was made possible by recent technological developments and access to satellite photographs. &nbsp

Violence in the ‘Ayn al-Hilweh Palestinian Refugee Camp in Lebanon, 2007–2009

Conditions in the Palestinian refugee camps in Lebanon are difficult, with poverty rates high, educational attainment low, and opportunities few. Of concern to policy-makers is ‘Ayn al-Hilweh, the largest camp in Lebanon. This camp experiences frequent factional violence and harbors numerous individuals wanted by Lebanese authorities. This study, using a random survey of households, examined the frequency of households’ experience with violence and the association of experiencing violence with PTSD symptomology. Results show one in five households experienced violence and these experiences were associated with increased PTSD symptomology. Implications for social work within the camp are discussed

Features of Child Food Insecurity after the 2010 Haiti Earthquake: Results from Longitudinal Random Survey of Households

<div><p>Background</p><p>Recent commentary on the health consequences of natural disasters has suggested a dearth of research on understanding the antecedents prior to the disaster that are associated with health consequences after the disaster. Utilizing data from a two-wave panel survey of Port-au-Prince, Haiti, conducted just prior to and six weeks after the January 2010 earthquake, we test factors prior to the quake hypothesized to be associated with food insecurity after the quake.</p><p>Methods</p><p>Using random Global Positioning System (GPS) sampling, we re-interviewed 93.1% (N = 1732) of the original 1,800 households interviewed in 2009. Respondents were queried with regard to mortalities, injuries, food security, housing, and other factors after the quake.</p><p>Findings</p><p>Child food insecurity was found to be common on all three indices of food security (17.2%–22.6%). Additionally, only 36.5% of school-aged children were attending school prior to the quake. Findings suggest that prior schooling was associated with a substantial reduction on food insecurity indices (OR 0.62–0.75). Findings further suggest that several household characteristics were associated with food insecurity for children. Prior chronic/acute illnesses, poor living conditions, remittances from abroad, primary respondent mental health, and histories of criminal and other human rights violations committed against family members prior to the quake were associated with food insecurity after the earthquake. Earned household income after the quake was only associated with one of the measures of food insecurity.</p><p>Interpretation</p><p>Food insecurity for children was common after the quake. Those households vulnerable on multiple dimensions prior to the quake were also vulnerable to food insecurity after the quake. Remittances from abroad were leading protective factors for food security. Because Haiti is well known for the potentiality of both hurricanes and earthquakes, reconstruction and redevelopment should focus on ameliorating potential vulnerabilities to poor outcomes in these natural disasters.</p></div

Logistic Regression of Cutting the Size of Children's Meals.

<p>***p<0.01,</p><p>**p<0.05,</p><p>*p<0.1.</p><p>Logistic Regression of Cutting the Size of Children's Meals.</p

Predictors of Whether the House had No Visible Damage following the Earthquake.

<p>***p<0.01,</p><p>**p<0.05,</p><p>*p<0.1, +p<.10.</p><p>Predictors of Whether the House had No Visible Damage following the Earthquake.</p

Descriptive Statistics, Children Aged 6 to 17, Weighted Percents and Means.

<p>Descriptive Statistics, Children Aged 6 to 17, Weighted Percents and Means.</p

Logistic Regression of the Probability that Child or Adolescent Aged 6 to 17 Was Attending School Prior to the Earthquake.

<p>***p<0.01,</p><p>**p<0.05,</p><p>*p<0.1.</p><p>Logistic Regression of the Probability that Child or Adolescent Aged 6 to 17 Was Attending School Prior to the Earthquake.</p

Logistic regression of the probability a child was hungry with and without household damage.

<p>***p<0.01,</p><p>**p<0.05,</p><p>*p<0.1.</p><p>Logistic regression of the probability a child was hungry with and without household damage.</p