DFID BLUE BOOK PDF

The Blue Book replaces the previous Red Book of guidelines for such surveys. The updated guidance keeps the global health community abreast of the evolving HIV epidemic, which has led to 37 million people currently living with HIV infection. Biobehavioral surveys provide population-level estimates for the burden of HIV disease and HIV-related risk factors, and they allow estimation of the coverage of prevention and treatment services for key populations that are at increased risk for HIV. Advances in available data and changes in the epidemic rendered the survey tools and guidelines in the Red Book out-of-date. In particular, there is an increased understanding of, and focus on, key populations. These key populations include men who have sex with men, sex workers, people who inject drugs, transgender individuals, prisoners and other vulnerable populations.

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The Blue Book replaces the previous Red Book of guidelines for such surveys. The updated guidance keeps the global health community abreast of the evolving HIV epidemic, which has led to 37 million people currently living with HIV infection. Biobehavioral surveys provide population-level estimates for the burden of HIV disease and HIV-related risk factors, and they allow estimation of the coverage of prevention and treatment services for key populations that are at increased risk for HIV.

Advances in available data and changes in the epidemic rendered the survey tools and guidelines in the Red Book out-of-date. In particular, there is an increased understanding of, and focus on, key populations. These key populations include men who have sex with men, sex workers, people who inject drugs, transgender individuals, prisoners and other vulnerable populations. For many of these stigmatized and socially marginalized populations, conventional sampling frames are unsatisfactory, requiring the use of complex sampling designs.

The updated guidelines cover all aspects of surveying key populations, with new emphases on these three objectives. Ideally for probability sampling, the sample selection process is randomization using a sampling frame. When it is not possible to get sampling frames of elementary units, other methods can be used to generate probability samples. The Red Book popularized the time-location, or time-space, sampling method.

Time-location clusters can be used when the populations included in surveillance come and go freely from sites, which may vary from day to day, and even by time of day or by the time of the month. Unfortunately, if people with various levels of risk visit a site at different times, then the time selected for sampling may affect the results of survey and make it less representative of the population as a whole.

For situations where hidden populations are prominent often due to illegal or highly stigmatized behaviors and time-location sampling is unlikely to be representative, the Red Book promoted non-probability methods including snowball or network sampling.

These non-probability methods result in convenience samples. See the right side of the Guest decision tree. While it was first introduced in by Douglas Heckathorn, RDS gained traction in behavioral and biological surveillance starting in thanks to this article by Salganik and Heckathorn. RDS is similar to snowball or chain-referral systems; however, by collecting data on social network size and limiting recruitment through using a set number of coupons, RDS obtains results that are generalizable for the population.

Salganik and Heckathorn demonstrate using mathematical theory that a sample reaches a probability sample after a sufficient number of waves recruitment chains have been reached. Figure 1: Sampling decision tree S. Mills et al. The jury is still out on whether RDS generates an actual probability-based sample, with some studies suggesting it may result in a sample that over-represents younger individuals of lower socio-economic status.

However, RDS currently represents the best available method for sampling hidden populations. The chain-referral process is also being used to good effect in social networking strategies for identifying new key populations in programmatic contexts. An important data need for addressing the targets , where the first target requires expanded HIV testing, is estimates of key population sizes.

Valid estimates of population sizes are important for understanding gaps in HIV testing coverage and for planning expanded access to HIV testing services. Population size is also important information for monitoring and evaluation efforts. The Blue Book integrates the latest thinking on population size estimation methods into the overall biobehavioral survey guidance. This integration takes advantage of the opportunity provided by biobehavioral surveys to include questions that can be triangulated with other data sources and used for size estimation purposes see in particular part 2b below.

Here is a selection of population estimation methods included in the Blue Book:. If they are not able to be sampled the second time, it introduces a bias to the multiplier calculation. An important requirement of the capture-recapture method is that the two data sources, i. This independence can be difficult to achieve in settings where key populations are highly stigmatized hidden , and access to their networks is extremely limited e.

It can be difficult and costly to implement with fidelity. Network scale-up is another method from general population surveys. It calculates population size by analyzing the proportion of members of a key population group those known to the respondent within the total personal network size of all people known to them personally.

Given the limitations of any single method, particularly in settings where key populations are hidden, mobile, and highly stigmatized, the gold standard is to apply three or more methods and triangulate the estimates to arrive at a more robust estimate, or one that can smooth out the various limitations of any single method. There are no hard and fast rules to arriving at estimates from triangulation. Consequently, the methodology for arriving at triangulated estimates should involve consensus building among relevant experts.

A good start is to bring methodological and key population experts together to review the strengths and weaknesses of each method in its local context and consider excluding methods deemed inadequate. The experts can review estimates that are extreme outliers, and then average the estimates deemed reliable, or present the results as a range between the lower and higher estimates.

The Red Book dealt exclusively with behavioral surveillance surveys, especially data from questionnaires. Subsequently, the emphasis in HIV surveillance has shifted towards second generation surveillance, which refers to interpreting behavioral together with biomarker data i. Use of biomarkers permits a comparison of information on HIV prevalence with data on the behaviors that spread the infection to create an informative picture of changes in the epidemic over time.

The types of biomarkers vary, but those of key interest include both HIV incidence and prevalence. The new guidance covers tests involving venous and dry blood, saliva, urine, and ano-rectal as well as endo-cervical swabs for STIs including: HSV-2, gonorrhea, chlamydia, trichomonas, syphilis, and hepatitis B and C virus. Other updates in the Blue Book include a new section on formative assessment, new survey questions around the global targets, questions around health service access and stigma, updated ethical guidance including conducting studies among incarcerated populations , as well as guidance around conducting surveys electronically.

The Blue Book also contains an expanded section on study monitoring tools and standard operating procedures and enhanced attention to disseminating and using the findings from studies. A forthcoming addition to the Blue Book will include ready-to-use electronic questionnaires specific for each key population and translations into French, Russian, and Spanish.

The updated Blue Book includes the best available guidance for collecting — and standardizing — data on HIV through biobehavioral surveys. The proliferation of biobehavioral survey studies in recent years among key population groups, particularly in sub-Saharan Africa, reflects a better understanding of the mixed nature of epidemics, including those classified as generalized.

These surveys increase our knowledge of the important links between members of key populations and the general population, and provide important new opportunities to inform comprehensive programs that leave no one behind in the quest to end AIDS.

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We use cookies to collect information about how you use GOV. We use this information to make the website work as well as possible and improve government services. You can change your cookie settings at any time. Find out useful information about how to do things at DFID, including rules and tools. PDF , KB , 11 pages.

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The guidance is divided into 2 sections. Definitions, design features and good practice for individual aid instruments and approaches: this section defines and describes individual aid instruments, focusing on key design features, strengths and weaknesses, evidence on performance, and best practice methods of delivery. It considers financial aid instruments Poverty Reduction Budget Support PRBS and non-PRBS financial aid to government , grants and other aid to non-government actors, technical cooperation, and policy engagement; and gives an overview of key approaches including programme-based approaches PBAs , sector-wide approaches SWAps , pooled funds, social funds, social transfers and challenge funds, and global funds and partnerships. The secondary audience is other UK government departments, international development partners e. It is broader in scope, including non-financial aid instruments such as technical cooperation and policy dialogue. It also takes into account policy shifts which have taken place since , giving more weight to issues such as country-led approaches, harmonisation, predictability and conditionality.

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