Assessing Network Scale-up Estimates for Groups Most at Risk of HIV/AIDS: Evidence From a Multiple-Method Study of Heavy Drug Users in Curitiba, Brazil

Salganik, Matthew J.; Fazito, Dimitri; Bertoni, Neilane; Abdo, Alexandre Hannud; Mello, Maeve B.; Bastos, Francisco I.

doi:10.1093/aje/kwr246

Cited by 85 publications

(142 citation statements)

References 31 publications

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“…Salganik et al estimated the number of heavy drug users in Curitiba, Brazil, using various methods [26]. Although by applying direct methods and multiplier method it was near to our estimates, using NSUM the size of MARPs was more than our estimates.…”

Section: At-risk Populationscontrasting

confidence: 47%

“…Based on the results of our study, the size of at-riskpopulations for AIDS in Tabriz is less than other areas [14,26,28]. Salganik et al estimated the number of heavy drug users in Curitiba, Brazil, using various methods [26].…”

Section: At-risk Populationsmentioning

confidence: 82%

“…In spite of this fact, we applied known population approach using maximum likelihood method. The main reason is the higher accuracy of this method in comparison with other methods which caused researchers in past studies to favor this method, as well [21,[23][24][25][26]. Because this method consists of active searching of respondents' memories and active memory searching usually leads to more accurate answers [21].…”

Section: Social Networkmentioning

confidence: 99%

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Size Estimation of Most-at-Risk Groups of HIV/AIDS Using Network Scale-up in Tabriz, Iran

et al. 2014

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Ab s t r a c tPurpose: To begin to manage a serious health problem like AIDS, it is crucial that we know the size of the subpopulation related to the problem. In this study we used Network scale-up method (NSUM), an indirect method of size estimation of hard-to-reach subpopulation, to estimate most-at-risk population (MARPs) of Tabriz. Methods:Having adapted a purposive sampling, we interviewed 500 people of target population. To estimate the size of social network (C), we used known population method through collecting data of 29 known sub-groups. To estimate most-at-risk populations, we applied frequency approach of NSUM. Adjustments were done to correct common errors of this method. Results:Among groups at risk due to sexual contact, the greatest frequency was related to clients of female sex workers (CFSWs) with 831 out of 100000 of men's population (95% CI: 649, 1055), then female sex workers (FSWs) with 709 out of 100000 of women's population (95% CI: 512, 930). Among groups at risk due to drug use, the biggest frequency belonged to alcoholic substance users with 1136 out of 100000 of total population (95% CI: 955, 1332). After that, it included opium users, crystal users and injecting drug users (IDUs), respectively. Conclusion:Although the estimated number of MARPs in Tabriz is less than other areas, it is necessary to perform preventive programs like harm reduction programs to reduce transmission of AIDS.

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Section: At-risk Populationscontrasting

confidence: 47%

Section: At-risk Populationsmentioning

confidence: 82%

Section: Social Networkmentioning

confidence: 99%

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Size Estimation of Most-at-Risk Groups of HIV/AIDS Using Network Scale-up in Tabriz, Iran

et al. 2014

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“…In light of the fact that the coverage of cancer registry in Iran is seriously defective, any prevalence estimation based on the incidence and survival rates retrieved from this data will, inevitably, be biased (Mohagheghi and Mosavi-Jarrahi, 2010;Zendehdel et al, 2010;Zendehdel et al, 2011;Ghojazadeh et al, 2013;Zendehdel, 2015). As a result, this study adopted a common method used for the estimations of different sub-populations (Salganik et al, 2011a).…”

Section: Discussionmentioning

confidence: 99%

Total and Partial Prevalence of Cancer Across Kerman Province, Iran, in 2014, Using an Adapted Generalized Network Scale-Up Method

Vardanjani¹,

Baneshi²,

Haghdoost³

2015

Asian Pacific Journal of Cancer Prevention

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Due to the lack of nationwide population-based cancer registration, the total cancer prevalence in Iran is unknown. Our previous work in which we used a basic network scale-up (NSU) method, failed to provide plausible estimates of total cancer prevalence in Kerman. The aim of the present study was to estimate total and partial prevalence of cancer in southeastern Iran using an adapted version of the generalized network scale-up method. A survey was conducted in 2014 using multi-stage cluster sampling. A total of 1995 face-to-face gender-matched interviews were performed based on an adapted version of the NSU questionnaire. Interviewees were asked about their family cancer history. Total and partial prevalence were estimated using a generalized NSU estimator. The Monte Carlo method was adopted for the estimation of upper/lower bounds of the uncertainty range of point estimates. One-yr, 2-3 yr, and 4-5 yr prevalence (per 100,000 people) was respectively estimated at 78 (95%CI, 66, 90), 128 (95%CI, 118, 147), and 59 (95%CI, 49, 70) for women, and 48 (95%CI, 38, 58), 78 (95%CI, 66, 91), and 42 (95%CI, 32, 52) for men. The 5-yr prevalence of all cancers was estimated at 0.18 percent for men, and 0.27 percent for women. This study showed that the generalized familial network scale-up method is capable of estimating cancer prevalence, with acceptable precision.

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“…Further research is needed to elucidate the extent to which the methods might be robust to their assumptions. Though prior studies have empirically compared estimation methods [16,34,35], only two studies to our knowledge have included the successive-sampling method [31,32].…”

Section: Introductionmentioning

confidence: 99%

Estimated Number of People Who Inject Drugs in San Francisco, 2005, 2009, and 2012

2015

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Allocation of resources to public health responses depends on having plausible estimates of the size of the population at risk. Unfortunately, the numbers of people who inject drugs (PWID) are difficult to estimate since injection drug use is highly stigmatized. Though estimation methods exist, the robustness of the methods to their assumptions is not well understood. Comparisons between methods are also lacking; information regarding the successive-sampling method is particularly scarce. The present study used several methods-including the successive-sampling method-to produce population size estimates from three rounds of cross-sectional surveys of PWID in San Francisco. It compares these estimates across time and across method. Our summary estimates are 10,158 for 2005, 15,554 for 2009, and 22,500 for 2012. Though the point summaries suggest an increasing population, considerable uncertainty is involved. Comparisons between and within methods reveal high variability, suggesting dependence on assumptions and analytic choices. We conclude that further research is needed to improve upon the estimation methods or develop entirely new ones. Meanwhile, plausible estimates can be achieved via multiple methods while avoiding the pitfall of relying on a single method that may be highly biased and highly imprecise.

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Assessing Network Scale-up Estimates for Groups Most at Risk of HIV/AIDS: Evidence From a Multiple-Method Study of Heavy Drug Users in Curitiba, Brazil

Cited by 85 publications

References 31 publications

Size Estimation of Most-at-Risk Groups of HIV/AIDS Using Network Scale-up in Tabriz, Iran

Size Estimation of Most-at-Risk Groups of HIV/AIDS Using Network Scale-up in Tabriz, Iran

Total and Partial Prevalence of Cancer Across Kerman Province, Iran, in 2014, Using an Adapted Generalized Network Scale-Up Method

Estimated Number of People Who Inject Drugs in San Francisco, 2005, 2009, and 2012

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