Household Demographic Surveillance System, Cause-Specific Mortality 1992-2012
World, 1992 - 2012
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Reference ID
WLD_1992-2012_INDEPTH_v01_M
Producer(s)
Osman A. Sankoh, Peter Byass, P. Kim Streatfield, Wasif A. Khan, Abba Bhuiya, Nurul Alam, Ali Sie, Abdramane Soura, Bassirou Bonfoh, Berhe Weldearegawi, Abraham Oduro, Margaret Gyapong, Momodou Jasseh, Siswanto Wilopo, Shashi Kant, Sanjay Juvekar, Thomas N. Williams, Frank O. Odhiambo, Alex Ezeh,
Created on
Dec 23, 2014
Last modified
Mar 29, 2019
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3652
Identification
Survey ID Number
WLD_1992-2012_INDEPTH_v01_M
Title
Household Demographic Surveillance System, Cause-Specific Mortality 1992-2012
Subtitle
Release 2014
Country
| Name | Country code |
|---|---|
| World | WLD |
Study type
Demographic Surveillance
Series Information
INDEPTH Cause of Death
Abstract
Cause of death data based on VA interviews were contributed by fourteen INDEPTH HDSS sites in sub-Saharan Africa and eight sites in Asia. The principles of the Network and its constituent population surveillance sites have been described elsewhere [1]. Each HDSS site is committed to long-term longitudinal surveillance of circumscribed populations, typically each covering around 50,000 to 100,000 people. Households are registered and visited regularly by lay field-workers, with a frequency varying from once per year to several times per year. All vital events are registered at each such visit, and any deaths recorded are followed up with verbal autopsy interviews, usually 147 undertaken by specially trained lay interviewers. A few sites were already operational in the 1990s, but in this dataset 95% of the person-time observed related to the period from 2000 onwards, with 58% from 2007 onwards. Two sites, in Nairobi and Ouagadougou, followed urban populations, while the remainder covered areas that were generally more rural in character, although some included local urban centres. Sites covered entire populations, although the Karonga, Malawi, site only contributed VAs for deaths of people aged 12 years and older. Because the sites were not located or designed in a systematic way to be representative of national or regional populations, it is not meaningful to aggregate results over sites.
All cause of death assignments in this dataset were made using the InterVA-4 model version 4.02 [2]. InterVA-4 uses probabilistic modelling to arrive at likely cause(s) of death for each VA case, the workings of the model being based on a combination of expert medical opinion and relevant available data. InterVA-4 is the only model currently available that processes VA data according to the WHO 2012 standard and categorises causes of death according to ICD-10. Since the VA data reported here were collected before the WHO 2012 standard was formulated, they were all retrospectively transformed into the WHO 2012 and InterVA-4 input format for processing.
The InterVA-4 model was applied to the data from each site, yielding, for each case, up to three possible causes of death or an indeterminate result. Each cause for a case is a single record in the dataset. In a minority of cases, for example where symptoms were vague, contradictory or mutually inconsistent, it was impossible for InterVA-4 to determine a cause of death, and these deaths were attributed as entirely indeterminate. For the remaining cases, one to three likely causes and their likelihoods were assigned by InterVA-4, and if the sum of their likelihoods was less than one, the residual component was then assigned as being indeterminate. This was an important process for capturing uncertainty in cause of death outcome(s) from the model at the individual level, thus avoiding over-interpretation of specific causes. As a consequence there were three sources of unattributed cause of death: deaths registered for which VAs were not successfully completed; VAs completed but where the cause was entirely indeterminate; and residual components of deaths attributed as indeterminate.
In this dataset each case has between one and four records, each with its own cause and likelihood. Cases for which VAs were not successfully completed has a single record with the cause of death recorded as “VA not completed” and a likelihood of one. Thus the overall sum of the likelihoods equated to the total number of deaths. Each record also contains a population weighting factor reflecting the ratio of the population fraction for its site, age group, sex and year to the corresponding age group and sex fraction in the standard population (see section on weighting).
In this context, all of these data are secondary datasets derived from primary data collected separately by each participating site. In all cases the primary data collection was covered by site-level ethical approvals relating to on-going demographic surveillance in those specific locations. No individual identity or household location data are included in this secondary data.
1. Sankoh O, Byass P. The INDEPTH Network: filling vital gaps in global epidemiology. International Journal of Epidemiology 2012; 41:579-588.
2. Byass P, Chandramohan D, Clark SJ, D’Ambruoso L, Fottrell E, Graham WJ, et al. Strengthening standardised interpretation of verbal autopsy data: the new InterVA-4 tool. Global Health Action 2012; 5:19281.
All cause of death assignments in this dataset were made using the InterVA-4 model version 4.02 [2]. InterVA-4 uses probabilistic modelling to arrive at likely cause(s) of death for each VA case, the workings of the model being based on a combination of expert medical opinion and relevant available data. InterVA-4 is the only model currently available that processes VA data according to the WHO 2012 standard and categorises causes of death according to ICD-10. Since the VA data reported here were collected before the WHO 2012 standard was formulated, they were all retrospectively transformed into the WHO 2012 and InterVA-4 input format for processing.
The InterVA-4 model was applied to the data from each site, yielding, for each case, up to three possible causes of death or an indeterminate result. Each cause for a case is a single record in the dataset. In a minority of cases, for example where symptoms were vague, contradictory or mutually inconsistent, it was impossible for InterVA-4 to determine a cause of death, and these deaths were attributed as entirely indeterminate. For the remaining cases, one to three likely causes and their likelihoods were assigned by InterVA-4, and if the sum of their likelihoods was less than one, the residual component was then assigned as being indeterminate. This was an important process for capturing uncertainty in cause of death outcome(s) from the model at the individual level, thus avoiding over-interpretation of specific causes. As a consequence there were three sources of unattributed cause of death: deaths registered for which VAs were not successfully completed; VAs completed but where the cause was entirely indeterminate; and residual components of deaths attributed as indeterminate.
In this dataset each case has between one and four records, each with its own cause and likelihood. Cases for which VAs were not successfully completed has a single record with the cause of death recorded as “VA not completed” and a likelihood of one. Thus the overall sum of the likelihoods equated to the total number of deaths. Each record also contains a population weighting factor reflecting the ratio of the population fraction for its site, age group, sex and year to the corresponding age group and sex fraction in the standard population (see section on weighting).
In this context, all of these data are secondary datasets derived from primary data collected separately by each participating site. In all cases the primary data collection was covered by site-level ethical approvals relating to on-going demographic surveillance in those specific locations. No individual identity or household location data are included in this secondary data.
1. Sankoh O, Byass P. The INDEPTH Network: filling vital gaps in global epidemiology. International Journal of Epidemiology 2012; 41:579-588.
2. Byass P, Chandramohan D, Clark SJ, D’Ambruoso L, Fottrell E, Graham WJ, et al. Strengthening standardised interpretation of verbal autopsy data: the new InterVA-4 tool. Global Health Action 2012; 5:19281.
Kind of Data
Verbal autopsy-based cause of death data
Unit of Analysis
Death Cause
Version
Version Description
Version 01: Base version
Version Date
2014-09-15
Scope
Notes
Cause of death derived from verbal autopsy interviews using automated anlysis by a computer program, InterVA 4.
Coverage
Geographic Coverage
Demographic surveiallance areas (countries from Africa, Asia and Oceania) of the following HDSSs:
<pre>Code Country INDEPTH Centre
BD011 Bangladesh ICDDR-B : Matlab
BD012 Bangladesh ICDDR-B : Bandarban
BD013 Bangladesh ICDDR-B : Chakaria
BD014 Bangladesh ICDDR-B : AMK
BF031 Burkina Faso Nouna
BF041 Burkina Faso Ouagadougou
CI011 Côte d'Ivoire Taabo
ET031 Ethiopia Kilite Awlaelo
GH011 Ghana Navrongo
GH031 Ghana Dodowa
GM011 The Gambia Farafenni
ID011 Indonesia Purworejo
IN011 India Ballabgarh
IN021 India Vadu
KE011 Kenya Kilifi
KE021 Kenya Kisumu
KE031 Kenya Nairobi
MW011 Malawi Karonga
SN011 Senegal IRD : Bandafassi
VN012 Vietnam Hanoi Medical University : Filabavi
ZA011 South Africa Agincourt
ZA031 South Africa Africa Centre </pre>
<pre>Code Country INDEPTH Centre
BD011 Bangladesh ICDDR-B : Matlab
BD012 Bangladesh ICDDR-B : Bandarban
BD013 Bangladesh ICDDR-B : Chakaria
BD014 Bangladesh ICDDR-B : AMK
BF031 Burkina Faso Nouna
BF041 Burkina Faso Ouagadougou
CI011 Côte d'Ivoire Taabo
ET031 Ethiopia Kilite Awlaelo
GH011 Ghana Navrongo
GH031 Ghana Dodowa
GM011 The Gambia Farafenni
ID011 Indonesia Purworejo
IN011 India Ballabgarh
IN021 India Vadu
KE011 Kenya Kilifi
KE021 Kenya Kisumu
KE031 Kenya Nairobi
MW011 Malawi Karonga
SN011 Senegal IRD : Bandafassi
VN012 Vietnam Hanoi Medical University : Filabavi
ZA011 South Africa Agincourt
ZA031 South Africa Africa Centre </pre>
Universe
Surveillance population Deceased individuals Cause of death
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Osman A. Sankoh | INDEPTH Network |
| Peter Byass | WHO Collaborating Centre for Verbal Autopsy, Umeå University |
| P. Kim Streatfield | Matlab, Bangladesh |
| Wasif A. Khan | Bandarban, Bangladesh |
| Abba Bhuiya | Chakaria, Bangladesh |
| Nurul Alam | AMK, Bangladesh |
| Ali Sie | Nouna, Burkina Faso |
| Abdramane Soura | Ouagadougou, Burkina Faso |
| Bassirou Bonfoh | Taabo, Côte d'Ivoire |
| Berhe Weldearegawi | Kilite-Awlaelo, Ethiopia |
| Abraham Oduro | Navrongo, Ghana |
| Margaret Gyapong | Dodowa, Ghana |
| Momodou Jasseh | Farafenni, The Gambia |
| Siswanto Wilopo | Purworejo, Indonesia |
| Shashi Kant | Ballabgarh, India |
| Sanjay Juvekar | Vadu, India |
| Thomas N. Williams | Kilifi, Kenya |
| Frank O. Odhiambo | Kisumu, Kenya |
| Alex Ezeh | Nairobi, Kenya |
| Amelia Crampin | Karonga, Malawi |
| Valérie Delaunay | Niakhar, Senegal |
| Stephen M. Tollman | Agincourt, South Africa |
| Abraham J. Herbst | Africa Centre, South Africa |
| Nguyen T.K. Chuc | FilaBavi, Vietnam |
| Marcel Tanner | Swiss Tropical and Public Health Institute |
Funding Agency/Sponsor
| Name |
|---|
| Bill & Melinda Gates Foundation |
| IDRC |
| Rockefeller Foundation |
| SIDA / Research Cooperation |
| Swiss TPH |
| Wellcome Trust |
| WHO/HMN |
| William and Flora Hewlett Foundation |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Kobus Herbst | INDEPTH Network | Dataset Production |
| Peter Byass | WHO Collaborating Centre for Verbal Autopsy, Umeå University | Dataset Production & Analysis |
| Samuelina Arthur | INDEPTH Network | Dataset Coordination |
Sampling
Sampling Procedure
No sampling, covers total population in demographic surveillance area
Weighting
The number of deaths by sex and age group were weighted using the INDEPTH 2013 standard population structure for low- and middle-income countries (LMICs) in Africa and Asia [1], as shown in Table 1. This public-domain standard population has been presented in relation to other global standards such as Segi and WHO, from which it differs in reflecting the higher fertility and younger-age mortality rates commonly seen in LMIC populations [1].
Each record contains a population weighting factor (wt) reflecting the ratio of the population fraction for its site, age group, sex and year to the corresponding age group and sex fraction in the standard population described in Table 1, for the purposes of standardisation. A further factor (lik_wt) is calculated for each record as the product of the VA cause likelihood and the population standard weighting (both described above), which can be used as the basis for calculating age-sex-time standardised CSMFs and CSMRs.
Table 1:
<pre>Age Group INDEPTH 2013 standard
Male Female
0-28 days 0.11% 0.10%
1-11 months 1.49% 1.38%
1-4 years 6.01% 5.57%
5-14 years 13.76% 12.57%
15-49 years 22.54% 23.50%
50-64 years 3.87% 4.36%
65+ years 2.22% 2.52%</pre>
1. Sankoh O, Sharrow D, Herbst K, Kabudula CW, Alam N, Kant S, et al. The INDEPTH standard population for low- and middle-income countries, 2013. Global Health Action 2014; 7:23286.
Each record contains a population weighting factor (wt) reflecting the ratio of the population fraction for its site, age group, sex and year to the corresponding age group and sex fraction in the standard population described in Table 1, for the purposes of standardisation. A further factor (lik_wt) is calculated for each record as the product of the VA cause likelihood and the population standard weighting (both described above), which can be used as the basis for calculating age-sex-time standardised CSMFs and CSMRs.
Table 1:
<pre>Age Group INDEPTH 2013 standard
Male Female
0-28 days 0.11% 0.10%
1-11 months 1.49% 1.38%
1-4 years 6.01% 5.57%
5-14 years 13.76% 12.57%
15-49 years 22.54% 23.50%
50-64 years 3.87% 4.36%
65+ years 2.22% 2.52%</pre>
1. Sankoh O, Sharrow D, Herbst K, Kabudula CW, Alam N, Kant S, et al. The INDEPTH standard population for low- and middle-income countries, 2013. Global Health Action 2014; 7:23286.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 1992-01-01 | 2012-12-31 |
Frequency of Data Collection
Rounds per year varies between sites from once to three times per year
Time periods
| Start date | End date |
|---|---|
| 1992-01-01 | 2012-12-31 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
Households are registered and visited regularly by lay field-workers, with a frequency varying from once per year to several times per year. All vital events are registered at each such visit, and any deaths recorded are followed up with verbal autopsy interviews, usually undertaken by specially trained lay interviewers.
Questionnaires
Questionnaires
The Verbal Autopsy Questionnaires used by the various sites differed, but in most cases they were a derivation from the original WHO Verbal Autopsy questionnaire.
http://www.who.int/healthinfo/statistics/verbalautopsystandards/en/index1.html
http://www.who.int/healthinfo/statistics/verbalautopsystandards/en/index1.html
Data Processing
Data Editing
One cause of death record was inserted for every death where a verbal autopsy was not conducted. The cuase of death assigned in these cases is "XX VA not completed"
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Kobus Herbst | INDEPTH Network | kherbst@africacentre.ac.za |
| Peter Byass | WHO Collaborating Centre for Verbal Autopsy, Umeå University | peter.byass@epiph.umu.se |
Access conditions
This data is made available for licensed access under the following conditions:
1. Data and other material provided by INDEPTH will not be redistributed or sold to other individuals, institutions or organisations without INDEPTH's written agreement.
2. In the case of multi-centre datasets, data originating from a single contributing member centre of the INDEPTH Network may not be analysed or reported on in isolation without the express permission of the member centre concerned.
3. No attempt will be made to re-identify respondents, and there will be no use of the identity of any person or establishment discovered inadvertently. Any such discovery will be reported immediately to INDEPTH.
4. No attempt will be made to produce links between datasets provided by INDEPTH or between INDEPTH data and other datasets that could identify individuals.
5. Any books, articles, conference papers, theses, dissertations, reports or other publications employing data obtained from INDEPTH will cite the source, in line with the citation requirement provided with the dataset.
6. An electronic copy of all publications based on the requested data will be sent to INDEPTH.
7. The original collector of the data, INDEPTH, and the relevant funding agencies bear no responsibility for the data's use or interpretation or inferences based upon it.
8. Any published use of the data must cite the dataset as specified under the citation requirements.
1. Data and other material provided by INDEPTH will not be redistributed or sold to other individuals, institutions or organisations without INDEPTH's written agreement.
2. In the case of multi-centre datasets, data originating from a single contributing member centre of the INDEPTH Network may not be analysed or reported on in isolation without the express permission of the member centre concerned.
3. No attempt will be made to re-identify respondents, and there will be no use of the identity of any person or establishment discovered inadvertently. Any such discovery will be reported immediately to INDEPTH.
4. No attempt will be made to produce links between datasets provided by INDEPTH or between INDEPTH data and other datasets that could identify individuals.
5. Any books, articles, conference papers, theses, dissertations, reports or other publications employing data obtained from INDEPTH will cite the source, in line with the citation requirement provided with the dataset.
6. An electronic copy of all publications based on the requested data will be sent to INDEPTH.
7. The original collector of the data, INDEPTH, and the relevant funding agencies bear no responsibility for the data's use or interpretation or inferences based upon it.
8. Any published use of the data must cite the dataset as specified under the citation requirements.
Citation requirements
INDEPTH Network. INDEPTH Network Cause-Specific Mortality - Release 2014. Oct 2014. Provided by the INDEPTH Network Data Repository. www.indepth-network.org <http://www.indepth-network.org>.10.7796/INDEPTH.GH003.COD2014.v1 <http://dx.doi.org/10.7796/INDEPTH.GH003.COD2014.v1>
Access authority
| Name | Affiliation | |
|---|---|---|
| Osman Sankoh | INDEPTH Network | osman.sankoh@indepth-network.org |
| Kobus Herbst | INDEPTH Network | kherbst@africacentre.ac.za |
Location of Data Collection
INDEPTH Data Repository
Archive where study is originally stored
INDEPTH Data Repository
http://www.indepth-ishare.org/index.php/catalog/48
Cose: None
http://www.indepth-ishare.org/index.php/catalog/48
Cose: None
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, INDEPTH, and the relevant funding agencies bear no responsibility for the data's use or interpretation or inferences based upon it.
Metadata production
DDI Document ID
DDI_WLD_1992-2012_INDEPTH_v02_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Kobus Herbst | KHe | INDEPTH Network | Study documentation |
| Peter Byass | PBy | INDEPTH Network | Study documentation |
Date of Metadata Production
2014-08-13
DDI Document version
Version 3 (22 Sep 2014)
Version 2 (15 Sep 2014)
Version 1 (13 Aug 2014)
Edited version, the original DDI (DDI.INDEPTH.GH003.COD2014.v2) was downloaded from INDEPTH Data Repository (http://www.indepth-ishare.org/index.php/catalog/central) on October 2014. The following DDI elements have been modified: DDI Document ID, survey ID and title of the study.
Version 2 (15 Sep 2014)
Version 1 (13 Aug 2014)
Edited version, the original DDI (DDI.INDEPTH.GH003.COD2014.v2) was downloaded from INDEPTH Data Repository (http://www.indepth-ishare.org/index.php/catalog/central) on October 2014. The following DDI elements have been modified: DDI Document ID, survey ID and title of the study.