AIDS Impact Survey III 2008 - Botswana

Abstract
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The primary objective of the 2008 BAIS III was to update current information on the behavioral patterns of the populations aged 10-64 years and the HIV prevalence and incidence rates among those aged 18 months and above at national, district and sub-district level. This information will be used for continuous strategic prevention and national HIV program planning and future HIV and AIDS research.

Specifically, the survey was intended to provide:
i. current national HIV prevalence and incidence estimates among the population aged 18 months and above;
ii. indicative trends in sexual and preventive behavior among the population aged 10-64 years;
iii. a comparison between HIV rate, behavior, knowledge, attitude, and cultural factors that are associated with the epidemic with estimates derived from previous surveys; and
iv. information on demographic, socio-economic, housing and household members' conditions associated with and/or are determinants and consequences of the pandemic.

A related objective is to produce survey results in a timely manner and ensure that the data are disseminated to a wide audience of potential users in government and non-governmental organizations within and outside Botswana as part of facilitation of broader effort to strengthen strategies aimed at combating the disease.

Geographic coverage
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National

Kind of data
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Sample survey data [ssd]

Sampling procedure
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The 2008 Botswana AIDS Impact Survey III (BAIS III) was designed to provide a comparison (trend) between HIV prevalence rate, behavior, knowledge, attitude, and other factors that are associated with the epidemic with estimates derived from previous survey, i.e. 2004 BAIS II.

Sampling Frame
For BAIS-II the sampling frame based on the 2001 Population and Housing Census. This comprised the list of all Enumeration Areas (EAs) together with number of households. In 2001 Census the EAs were framed of manageable size (in terms of dwellings/households). So, the primary sampling units (PSUs) were EAs.

Stratification
Stratification was undertaken such that all districts and major urban centers become their own strata. With regard to increase precision consideration was also given to group EAs according to ecological zones in rural districts and according to income categories in cities/towns. Geographical stratification along ecological zones and income categories was expected to improve the accuracy of survey data in view that homogeneity of the variables within stratum was relatively high.

Sample Design
A stratified two-stage probability sample design was used for the selection of the sample.

The first stage was the selection of EAs as Primary Sampling Units (PSUs) selected with probability proportional to measures of size (PPS), where measures of size (MOS) were the number of households in the EA as defined by the 2001 Population and Housing Census. In all 459 EAs were selected with probability proportional to size.

At the second stage of sampling, the households were systematically selected from fresh list of occupied households prepared at the beginning of the survey's fieldwork (i.e. listing of households for the selected EAs). Overall 8,275 households were drawn systematically.

Note: See detailed sampling information in BAIS-III final report.

Mode of data collection
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Face-to-face [f2f]

Research instrument
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The questionnaires are the primary recording documents of the survey. In the development of the questionnaires, along with the professionals, the other members (Including some users) were also invited. The final version of the questionnaires was finalized on the basis of the experiences aimed from the pretest conducted using the drafted questionnaires for the survey.

The 208 BAIS III has three major components, namely the Household Questionnaire, the Individual Questionnaire and the Blood Collection Form.

The Household Questionnaire was used to list all members of the selected households and their demographic characteristics such as age, sex, orphan hood (0-17 years) and economic activity.

The Individual Questionnaire was designed to capture information regarding demographic characteristics, care and support, marriage and cohabiting partnerships, alcohol consumption and drug use, sexual history and behavior, male circumcision and sexually transmitted diseases, knowledge about HIV/AIDS and level of interventions, attitudes towards people with HIV/AIDS, childbearing and antenatal care as well as availability of social and medical services in response to the pandemic.

The third component is on the scale of the pandemic. It was designed to collect blood samples from members of households aged 18 months and over for testing and estimation of HIV prevalence and derivation of incidence measures.

Cleaning operations
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Before data entry was carried out, the questionnaires were edited to check if all the relevant questions have been responded to and coded according to the codes designed for the study. Editing and coding started in July 2007 and finished in February 2008. Data entry was carried out under the supervision of one programmer/supervisor. Consistency checks on the data set as per the computer edit specifications designed by the subject matter specialists were performed.

Sampling error estimates
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SAMPLING ERRORS
The estimates from a sample survey are affected by two types of errors: (1) non-sampling error, and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2008 BAIS III to minimize these type of errors, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2008 BAIS III is only one of many samples that could have been selected from the same population, using the same sample design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

The standard error can also be used to compute the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1 indicates that the sample design is as efficient as simple random sample: a value greater than 1 indicates that increase in the sampling error is due to the use of more complex and less statistically efficient design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulae for calculating standard errors. However, the BFHS sample is the results of a stratified two stage design which is considered a complex design, hence special methods and software's are required to take into account the complexity of the design.

WesVar 4.3 statistical software (supported by WESTAT) was used to obtain standard errors, confidence intervals and design effect for selected indicators. It is a powerful tool for statistical data analysis from complex survey designs which includes multi-stage, stratification and unequal probability samples. Jackknife replication method was applied which forms part of the replication options within this software. To estimate variances using the jackknife method requires forming replications from the full sample by randomly eliminating one sample cluster (enumeration area) from a domain or stratum at a time. Then a pseudo-estimate is formed from the retained EAs, which are re-weighted to compensate for the eliminated unit. Thus, for a particular stratum containing k clusters, k replicated estimates are formed by eliminating one of these, at a time, and increasing the weight of the remaining (k - 1) clusters by a factor of k /(k - 1). This process is repeated for each cluster.

Note: See detailed sampling error calculation which is presented in 2008 BAIS-III final report.

摘要
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2008年BAIS III的主要目标是在国家、地区和次地区层面更新10-64岁人群的行为模式以及18个月及以上人群的HIV流行率和发病率的相关信息。这些信息将被用于持续的预防战略规划、国家HIV项目规划以及未来的HIV和AIDS研究。
具体而言，该调查旨在提供以下内容：
i. 18个月及以上人群中当前国家HIV流行率和发病率的估计值；
ii. 10-64岁人群中性传播和预防行为的变化趋势；
iii. 与先前调查（如2004年BAIS II）得出的估计值相比，HIV率、行为、知识、态度以及与文化因素相关的流行病相关因素的比较；
iv. 与流行病相关及/或为流行病决定因素和后果的与人口统计、社会经济、住房和家庭成员状况相关的信息。
一个相关目标是及时生成调查结果，并确保数据在博茨瓦纳国内外政府和非政府组织的广大潜在用户中传播，作为加强旨在对抗疾病的战略的更广泛努力的辅助。
地理覆盖范围
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全国
数据类型
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样本调查数据 [ssd]
抽样程序
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2008年博茨瓦纳艾滋病影响调查III（BAIS III）旨在提供HIV流行率、行为、知识、态度以及其他与流行病相关的因素的比较（趋势），这些因素与先前调查（即2004年BAIS II）得出的估计值进行比较。
抽样框
对于BAIS-II，抽样框基于2001年人口和住房普查。这包括所有统计区域（EA）的名单以及家庭数量。在2001年普查中，EA被设计为可管理的规模（就住宅/家庭而言）。因此，一级抽样单位（PSU）是EA。
分层
分层旨在使所有地区和主要城市中心成为其自身的层。关于提高精度的考虑，还对农村地区的生态区和城市/镇的收入类别进行了EA分组。在生态区和收入类别上进行的地理分层预计将提高调查数据的准确性，因为在层内的变量同质性相对较高。
样本设计
使用了分层两阶段概率样本设计来选择样本。
第一阶段是选择EA作为一级抽样单位（PSU），以规模比例（PPS）选择，其中规模比例（MOS）是根据2001年人口和住房普查定义的EA中的家庭数量。总共选择了459个EA，其选择概率与规模成比例。
在抽样的第二阶段，从调查现场工作开始时准备的新鲜家庭名单中系统地选择了家庭。总共抽取了8,275个家庭。
注意：有关详细的抽样信息，请参阅BAIS-III最终报告。
数据收集方式
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面对面 [f2f]
研究工具
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问卷是调查的主要记录文件。在问卷的开发过程中，除了专业人士外，其他成员（包括一些用户）也被邀请参与。最终版本的问卷是在基于使用草拟的问卷进行的预测试所获得的经验的基础上确定的。
2008年BAIS III包含三个主要组成部分，即家庭问卷、个人问卷和血液采集表。
家庭问卷用于列出所选家庭的全部成员及其人口统计特征，如年龄、性别、孤儿状况（0-17岁）和经济活动。
个人问卷旨在收集有关人口统计特征、护理和支持、婚姻和同居伙伴关系、酒精消费和药物使用、性史和行为、男性割礼和性传播疾病、关于HIV/AIDS的知识和干预水平、对HIV/AIDS患者态度、生育和产前护理以及应对大流行的社会和医疗服务可用性的信息。
第三部分关于大流行的规模。它旨在从18个月及以上的家庭成员中收集血液样本进行检测和估计HIV流行率，并推导发病率指标。
数据清洗操作
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在数据录入之前，对问卷进行了编辑，以检查是否所有相关问题都已回答，并根据研究设计的代码进行编码。编辑和编码始于2007年7月，并于2008年2月完成。数据录入在一名程序员/监督员的监督下进行。根据主题专家设计的计算机编辑规范对数据集进行了一致性检查。
抽样误差估计
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抽样误差
样本调查的估计值受到两种类型误差的影响：（1）非抽样误差，和（2）抽样误差。非抽样误差是数据收集和数据处理中错误的结果，例如未能找到和采访正确的家庭、采访者或受访者对问题的误解，以及数据录入错误。尽管在实施2008年BAIS III期间做出了众多努力以尽量减少此类误差，但非抽样误差不可避免且难以进行统计分析。
另一方面，抽样误差可以通过统计方法进行评估。2008年BAIS III中选择的受访者样本只是从同一人口中选择的许多样本之一，使用相同的样本设计和预期规模。这些样本中的每一个都会产生与实际选定的样本结果略有不同的结果。抽样误差是所有可能样本之间差异的度量。尽管变异的程度无法确切知道，但它可以从调查结果中估计出来。
抽样误差通常用特定统计量（均值、百分比等）的标准误差来衡量，它是方差的平方根。标准误差可用于计算置信区间，其中可以合理地假设真实值落在该区间内。例如，对于从样本调查中计算的任何给定统计量，该统计量的值将在95%的所有可能样本中落在该统计量的标准误差的两倍范围内。
标准误差还可以用于计算每个估计值的设计效应（DEFT），它定义为使用给定样本设计计算的标准误差与使用简单随机样本计算的标准误差之间的比率。DEFT值为1表示样本设计与简单随机样本一样高效：值大于1表示抽样误差的增加是由于使用了更复杂且统计效率较低的样本设计。
如果受访者样本被选择为简单随机样本，则可以使用简单的公式来计算标准误差。然而，BFHS样本是分层两阶段设计的产物，被认为是一种复杂的设计，因此需要特殊的方法和软件来考虑设计的复杂性。
WesVar 4.3统计软件（由WESTAT支持）用于获得标准误差、置信区间和设计效应。它是分析复杂调查设计（包括多阶段、分层和不等概率样本）的强大工具。Jackknife复制方法被应用，这是该软件复制选项的一部分。要使用Jackknife方法估计方差，需要从整个样本中随机消除一个样本聚类（统计区域），然后从领域或层中一次形成伪估计。然后，从保留的EA中形成伪估计，并将其重新加权以补偿消除的单位。因此，对于包含k个聚类的特定层，通过每次消除其中一个并增加剩余的（k - 1）个聚类的权重k / (k - 1)倍，形成k个复制估计值。这个过程对每个聚类重复进行。
注意：有关抽样误差计算的具体细节，请参阅2008年BAIS-III最终报告。