|Year : 2020 | Volume
| Issue : 5 | Page : 67-70
Did Inclusion of informed consent affect the observed hiv prevalence rate among injecting drug users during hiv sentinel surveillance 2017 in Delhi, Uttar Pradesh, Uttarakhand, and Jharkhand States of Central Zone of India?
Sanjay Kumar Rai1, Farhad Ahamed2, Shashi Kant3, Partha Haldar4, Shreya Jha5, Shobini Rajan6
1 Professor, Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
2 Assistant Professor, Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Kalyani, West Bengal, India
3 Professor and Head, Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
4 Associate Professor, Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
5 Consultant, Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
6 Assistant Director General, National AIDS Control Organization, MoHFW, GOI, New Delhi, India
|Date of Submission||30-Oct-2019|
|Date of Decision||21-Jan-2020|
|Date of Acceptance||25-Feb-2020|
|Date of Web Publication||14-Apr-2020|
Dr. Farhad Ahamed
Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Kalyani, West Bengal
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: In 2017, the sampling procedure for HIV sentinel surveillance (HSS) among all high-risk groups was changed from the consecutive sampling to random sampling along with the introduction of linked anonymous testing strategy with informed written consent. Objective: The objective of this study was to assess whether the inclusion of informed consent affects the HIV positivity rate among the participants and nonparticipants injecting drug users (IDU) in HSS 2017 in four states of Central Zone of India. Methods: This study was a cross-sectional study. All sentinel sites from Delhi, Uttar Pradesh, Jharkhand, and Uttarakhand located at targeted intervention facilities in 2017 were included in the study. Information about the participation and nonparticipation of each high-risk individual at the sentinel site was gathered from the master list, respective registers, and website portal of the National AIDS Control Organization. A total of 8639 individuals were included in the analysis. Results: Overall, 16 sites in four states were included in the study. Overall, the nonparticipation rate of IDUs was 14.3%; highest being for Delhi (17.2%), followed by Uttar Pradesh (14.6%), Uttarakhand (10.9%), and Jharkhand (4.4%). Overall, the HIV-positivity rate among nonparticipants (9.6%) was significantly higher (P = 0.009) compared to the participants (6.7%). Conclusion: Change in methodology and seeking written informed consent might have an effect on the nonparticipation in all four states. This, in turn, could have led to the underestimation of HIV-positivity rates among IDU in the states.
Keywords: HIV prevalence, HIV sentinel surveillance, injecting drug users
|How to cite this article:|
Rai SK, Ahamed F, Kant S, Haldar P, Jha S, Rajan S. Did Inclusion of informed consent affect the observed hiv prevalence rate among injecting drug users during hiv sentinel surveillance 2017 in Delhi, Uttar Pradesh, Uttarakhand, and Jharkhand States of Central Zone of India?. Indian J Public Health 2020;64, Suppl S1:67-70
|How to cite this URL:|
Rai SK, Ahamed F, Kant S, Haldar P, Jha S, Rajan S. Did Inclusion of informed consent affect the observed hiv prevalence rate among injecting drug users during hiv sentinel surveillance 2017 in Delhi, Uttar Pradesh, Uttarakhand, and Jharkhand States of Central Zone of India?. Indian J Public Health [serial online] 2020 [cited 2020 May 29];64, Suppl S1:67-70. Available from: http://www.ijph.in/text.asp?2020/64/5/67/282412
| Introduction|| |
An estimated 37.9 million people were living with HIV/AIDS globally in 2018, of which approximately 2.1 million were from India. The prevalence and trend of HIV/AIDS in India are monitored by the biennial HIV sentinel surveillance (HSS) among different population groups since 1998. The 15th round of HSS was conducted in 2017, wherein four high-risk groups (HRGs), namely injecting drug users (IDUs), female sex workers, men having sex with men, and hijra/transgender were included.
India had a concentrated epidemic of HIV, i.e., most of the HIV infection and transmission were concentrated among persons with high-risk behavior. IDUs were one of the HRGs and an important driver of the HIV epidemic in India. The prevalence and trend of HIV infection in this group are used by the policy-makers for resource allocation, strategy formulation, and monitoring the progress in program implementation among others.
Before the year 2017, the HSS among HRG in Central Zone states was conducted by the consecutive sampling technique with unlinked anonymous testing strategy.,, The blood was collected consecutively from eligible participants reporting to the sentinel sites. The blood was collected primarily for clinical test purposes, and the HIV testing was done on an aliquot of this blood sample. The National AIDS Control Organization (NACO) in 2017 changed the sampling procedure from consecutive sampling to random sampling to select the eligible participants. In addition to this, it adopted a linked anonymous testing strategy with informed written consent for HSS to ensure that the participants who tested positive could be traced back and offered treatment. The revised HSS method was adopted in the five states of Central India that were supervised by the Regional Institute All India Institute of Medical Sciences (AIIMS) in 2017.
The change in strategy was designed to achieve the two objectives. First, there was a moral and ethical imperative to offer the treatment to those who test positive for HIV. Hence, the link test strategy was needed. As a corollary, one would also require written informed consent. Second, in order to ensure that the observed HIV prevalence rate is more robust, a representative sample was required. The same was attempted by resorting to a random sampling technique.
We hypothesized that the change in sampling strategy and the need to administer written informed consent could potentially affect the participation rate in HSS, thereby impacting the observed prevalence and trend of HIV infection. Therefore, we undertook this study to assess whether the inclusion of informed consent affects the HIV-positivity rate among participants and nonparticipants IDU in HSS 2017 in four states of Central Zone of India.
| Materials and Methods|| |
All IDU sentinel sites located in the five states of India (Bihar [n = 2], Delhi [n = 3], Jharkhand [n = 1], Uttar Pradesh [n = 11], and Uttarakhand [n = 1]) that constituted the Central zone of HSS were eligible to be included in the study. Bihar state was excluded from this study due to operational reasons. The sentinel sites were located at targeted intervention (TI) facilities operated by the Non-Governmental Organizations. A total of 16 sentinel sites from the states of Delhi, Jharkhand, Uttar Pradesh, and Uttarakhand were included in the study.
This study was conducted in the year 2017.
At each sentinel site, 250 IDUs were recruited. An interview schedule that included demographic information and HIV-related risk behavior was administered followed by the collection of blood specimen.
Data collection during HIV sentinel surveillance at targeted intervention sites
Each TI site maintained a computerized listing of all high-risk individuals (HRIs) who were ever-contacted and registered for TI. This list was called “Master List”. From the respective State AIDS Control Society (SACS), each TI site received a random list of 250 HRIs drawn randomly from the master list. Peer educator (PE) made attempt to contact the HRI in the list. Those HRI who could be contacted were asked to visit the sentinel site along with the PE. The personal details of the HRI were entered in the HSS register, and eligibility for participation in HSS was assessed. Informed written consent was sought from the eligible HRI for their participation in HSS. HRI that refused to participate or could not be contacted even after three attempts by PE were classified as “nonparticipants.”
Data sources for the study
For this study, data were obtained from the three sources: (i) Master list with HIV test result of HRIs to know the HIV status of the nonparticipants, (ii) HSS register to know the extent of nonparticipation, and (iii) Website portal of NACO Strategic Information Management System (SIMS) database, which provided the HIV status of the participants. Information regarding the participation of selected HRI and master list were obtained from the sentinel sites through SACS. Information related to HIV status as of April 2017, participation in HSS, and adherence to the random list were extracted from the above-listed data sources.
Selected HRIs who could not be contacted even after three separate attempts were labeled as “noncontactable.” Those HRIs who were contacted but did not agree to participate in HSS were labeled as “refused.” The details of all the noncontactable and those who refused (along with the reason for refusal) were recorded in the HSS register. Noncontactable and those who refused to participate in HSS together constituted “nonparticipants.”
All HRIs who participated in HSS 2017 whether from the random list or selected by the TI partner even if outside of random list were labeled as “participants.” Details of the participants were downloaded from the website portal of NACO SIMS.
Quality control of HIV sentinel surveillance
Data from the physical paper-based forms were entered into the web-based software called SIMS twice by two separate data entry operators. Dual data were matched to identify mismatched entry which was resolved by referring to the original paper-based data. All HIV positive and 5% of the HIV-negative blood samples selected randomly were sent from the State Reference Laboratory to the National Reference Laboratory (NRL) located at the National AIDS Research Institute, Pune, India. NRL independently rechecked HIV status of the blood samples as a quality control mechanism under the External Quality Assurance Scheme. All data forms with HIV-positive results were cross-checked with the data entered in the computerized information management system as part of the quality check. For this study, quality control was ensured by the reconciliation of information collected in consultation with TI sites.
After merging and matching the data, statistical analysis was performed using STATA-12 software (StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP). All qualitative variables were expressed in terms of percentage with a 95% confidence interval. The Chi-square test was performed, and P ≤ 0.05 was considered statistically significant.
Ethical approval was obtained from the Institutional Ethics Committee of AIIMS, New Delhi, India.
| Results|| |
A total of 16 IDU sites were included in the analysis from the states of Delhi, Jharkhand, UP, and Uttarakhand (3, 1, 11, and 1 sites, respectively). Nonparticipation rate was the highest for Delhi (17.2%), followed by UP (14.6%), and Uttarakhand (10.9%). Jharkhand had the lowest nonparticipation rate (4.4%) among the four states [Table 1].
|Table 1: State-wise distribution of participants and non-participants in HIV Sentinel Surveillance-2017|
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In Delhi, the HIV-positivity rate among the nonparticipants (11.5%) was lower than that of the participants (16.4%) (P = 0.128). In Jharkhand, the HIV-positivity rate was nearly similar among participants (0.4%) and nonparticipants (0.0%) (P = 0.830). The HIV-positivity rate was significantly higher (P = 0.011) among nonparticipants (7.3%) as compared to participants (4.5%) in UP. Similarly, in Uttarakhand, the HIV-positivity rate was significantly higher (P < 0.001) among nonparticipants (40.0%) as compared to participants (9.0%). Overall, the HIV-positivity rate among nonparticipants (9.6%) was significantly higher (P = 0.009) compared to 6.8% among the participants [Table 2].
|Table 2: State-wise distribution of HIV prevalence among participants and non-participants in HIV Sentinel Surveillance-2017|
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| Discussion|| |
During HSS-2017, the sampling strategy was changed from consecutive sampling with unlinked anonymous testing to random sampling with linked anonymous testing and informed written consent. In this study, we aimed to find out whether this change in strategy, especially seeking informed written consent had any effect on the observed HIV prevalence rate among the IDUs of the states of Delhi, Jharkhand, Uttarakhand, and UP.
The nonparticipation rate varied greatly between the states. The nonparticipation rate among IDUs was highest (17.2%) in Delhi, while it was lowest in Jharkhand (4.4%). One possible reason for nonparticipation could be that those IDUs who knew that they were HIV positive were less inclined to get tested again. As HIV seropositivity rate among IDU in Delhi was very high (16.4%) compared to Jharkhand (0.4%), the nonparticipation rate was accordingly high in Delhi compared to Jharkhand. The observed HIV prevalence rate would get biased if the nonparticipation is based on any specific factor.
The HIV prevalence rate among nonparticipants was significantly higher than the participants in two out of the four states included in the study. Overall, the HIV prevalence rate among nonparticipants was 3% higher compared to the participants (9.6% vs. 6.7%). One possible reason for this could be the selective refusal by HRIs who knew their HIV-positive status. These HIV-positive HRI may not have perceived any added benefit by participating in the HSS. Selective nonparticipation of HIV-positive HRI had thus led to underestimation of HIV prevalence rate.
The first objective was met. However, the findings directly challenge the second objective, i.e., representativeness. The high nonparticipation rate virtually ruled out the representativeness of the sample. We also show that nonrepresentativeness led to underestimating the HIV-positive rate in Central Zone.
This was the first study to describe the difference of HIV prevalence between the participants and nonparticipants. This study also indirectly assessed the quality of data collected during HSS-2017. The assessment was done quantitatively which can now be used for the comparison in future. Due to the logistic reasons, Bihar state was excluded impacting the completeness of assessment for Central Zone as one unit. In participants, the HIV status was checked during the recruitment of the study, and in case of nonparticipants, the status was verified from the records at TI. However, the same testing strategy was used in both the groups, and it is unlikely that there will be a difference in the quality of data. Hence, the results are comparable in both groups. There might be other factors contributing to the study findings. However, those were beyond the scope of our study.
| Conclusion|| |
Differential participation rate based on known HIV status poses a serious challenge to the representativeness of the observed finding. The change in sampling strategy and introducing informed consent for recruitment of HRGs in HSS-2017 round can lead to the underestimation of numbers of HIV-infected IDUs in Central Zone.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
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[Table 1], [Table 2]