{"type":"survey","doc_desc":{"title":"INDEPTH Network Cause-Specific Mortality - Release 2014","idno":"DDI_WLD_1992-2012_INDEPTH_v02_M","producers":[{"name":"Kobus Herbst","abbreviation":"KHe","affiliation":"INDEPTH Network","role":"Study documentation"},{"name":"Peter Byass","abbreviation":"PBy","affiliation":"INDEPTH Network","role":"Study documentation"}],"prod_date":"2014-08-13","version_statement":{"version":"Version 3 (22 Sep 2014)\nVersion 2 (15 Sep 2014)\nVersion 1 (13 Aug 2014)\n\nEdited 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_notes":"Version 1. Kobus Herbst. Base version\nVersion 2. Kobus Herbst. Fixed standard population table. Added Funders. Added weight formulas\nVersion 3. Kobus Herbst. Changed country to Africa & Asia, changed geographic coverage"}},"study_desc":{"title_statement":{"idno":"WLD_1992-2012_INDEPTH_v01_M","title":"Household Demographic Surveillance System, Cause-Specific Mortality 1992-2012","sub_title":"Release 2014","alt_title":"INDEPTH 1992-12"},"authoring_entity":[{"name":"Osman A. Sankoh","affiliation":"INDEPTH Network"},{"name":"Peter Byass","affiliation":"WHO Collaborating Centre for Verbal Autopsy, Ume\u00e5 University"},{"name":"P. Kim Streatfield","affiliation":"Matlab, Bangladesh"},{"name":"Wasif A. Khan","affiliation":"Bandarban, Bangladesh"},{"name":"Abba Bhuiya","affiliation":"Chakaria, Bangladesh"},{"name":"Nurul Alam","affiliation":"AMK, Bangladesh"},{"name":"Ali Sie","affiliation":"Nouna, Burkina Faso"},{"name":"Abdramane Soura","affiliation":"Ouagadougou, Burkina Faso"},{"name":"Bassirou Bonfoh","affiliation":"Taabo, C\u00f4te d'Ivoire"},{"name":"Berhe Weldearegawi","affiliation":"Kilite-Awlaelo, Ethiopia"},{"name":"Abraham Oduro","affiliation":"Navrongo, Ghana"},{"name":"Margaret Gyapong","affiliation":"Dodowa, Ghana"},{"name":"Momodou Jasseh","affiliation":"Farafenni, The Gambia"},{"name":"Siswanto Wilopo","affiliation":"Purworejo, Indonesia"},{"name":"Shashi Kant","affiliation":"Ballabgarh, India"},{"name":"Sanjay Juvekar","affiliation":"Vadu, India"},{"name":"Thomas N. Williams","affiliation":"Kilifi, Kenya"},{"name":"Frank O. Odhiambo","affiliation":"Kisumu, Kenya"},{"name":"Alex Ezeh","affiliation":"Nairobi, Kenya"},{"name":"Amelia Crampin","affiliation":"Karonga, Malawi"},{"name":"Val\u00e9rie Delaunay","affiliation":"Niakhar, Senegal"},{"name":"Stephen M. Tollman","affiliation":"Agincourt, South Africa"},{"name":"Abraham J. Herbst","affiliation":"Africa Centre, South Africa"},{"name":"Nguyen T.K. Chuc","affiliation":"FilaBavi, Vietnam"},{"name":"Marcel Tanner","affiliation":"Swiss Tropical and Public Health Institute"}],"oth_id":[{"name":"Kobus Herbst","affiliation":"INDEPTH Network","email":"","role":"Dataset Production"},{"name":"Peter Byass","affiliation":"WHO Collaborating Centre for Verbal Autopsy, Ume\u00e5 University","email":"","role":"Dataset Production & Analysis"},{"name":"Samuelina Arthur","affiliation":"INDEPTH Network","email":"","role":"Dataset Coordination"}],"production_statement":{"funding_agencies":[{"name":"Bill & Melinda Gates Foundation","abbreviation":"","role":""},{"name":"IDRC","abbreviation":"","role":""},{"name":"Rockefeller Foundation","abbreviation":"","role":""},{"name":"SIDA \/ Research Cooperation","abbreviation":"","role":""},{"name":"Swiss TPH","abbreviation":"","role":""},{"name":"Wellcome Trust","abbreviation":"","role":""},{"name":"WHO\/HMN","abbreviation":"","role":""},{"name":"William and Flora Hewlett Foundation","abbreviation":"","role":""}]},"distribution_statement":{"contact":[{"name":"Kobus Herbst","affiliation":"INDEPTH Network","email":"kherbst@africacentre.ac.za","uri":""},{"name":"Peter Byass","affiliation":"WHO Collaborating Centre for Verbal Autopsy, Ume\u00e5 University","email":"peter.byass@epiph.umu.se","uri":""}]},"series_statement":{"series_name":"Demographic Surveillance","series_info":"INDEPTH Cause of Death"},"version_statement":{"version":"Version 01: Base version","version_date":"2014-09-15"},"holdings":[{"text":"","location":"","callno":"","uri":"dx.doi.org\/10.7796\/INDEPTH.GH003.COD2014.v1"}],"study_info":{"topics":[{"topic":"Cause of Death [N01.224.935.698.100]","vocab":"MeSH","uri":"http:\/\/www.ncbi.nlm.nih.gov\/mesh"},{"topic":"Mortality [N01.224.935.698]","vocab":"MeSH","uri":"http:\/\/www.ncbi.nlm.nih.gov\/mesh"}],"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.\n\nAll 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.\n\nThe 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.\n\nIn 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 \u201cVA not completed\u201d 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).\n\nIn 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.\n\n1. Sankoh O, Byass P. The INDEPTH Network: filling vital gaps in global epidemiology. International Journal of Epidemiology 2012; 41:579-588.\n\n2. Byass P, Chandramohan D, Clark SJ, D\u2019Ambruoso 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.","time_periods":[{"start":"1992-01-01","end":"2012-12-31","cycle":""}],"coll_dates":[{"start":"1992-01-01","end":"2012-12-31","cycle":""}],"nation":[{"name":"World","abbreviation":"WLD"}],"geog_coverage":"Demographic surveiallance areas (countries from Africa, Asia and Oceania) of the following HDSSs:\n<pre>Code   Country        INDEPTH Centre\t\nBD011  Bangladesh     ICDDR-B : Matlab\t\nBD012  Bangladesh     ICDDR-B : Bandarban\t\nBD013  Bangladesh     ICDDR-B : Chakaria\t\nBD014  Bangladesh     ICDDR-B : AMK\t\nBF031  Burkina Faso   Nouna\t\nBF041  Burkina Faso   Ouagadougou\t\nCI011  C\u00f4te d'Ivoire  Taabo\t\nET031  Ethiopia       Kilite Awlaelo\t\nGH011  Ghana          Navrongo\t\nGH031  Ghana          Dodowa\t\nGM011  The Gambia     Farafenni\t\nID011  Indonesia      Purworejo\t\nIN011  India          Ballabgarh\t\nIN021  India          Vadu\t\nKE011  Kenya          Kilifi\t\nKE021  Kenya          Kisumu\t\nKE031  Kenya          Nairobi\t\nMW011  Malawi         Karonga\t\nSN011  Senegal        IRD  : Bandafassi\t\nVN012  Vietnam        Hanoi Medical University : Filabavi\t\nZA011  South Africa   Agincourt\t\nZA031  South Africa   Africa Centre\t<\/pre>","analysis_unit":"Death Cause","universe":"Surveillance population Deceased individuals Cause of death","data_kind":"Verbal autopsy-based cause of death data","notes":"Cause of death derived from verbal autopsy interviews using automated anlysis by a computer program, InterVA 4.","study_scope":"Cause of death derived from verbal autopsy interviews using automated anlysis by a computer program, InterVA 4."},"method":{"data_collection":{"frequency":"Rounds per year varies between sites from once to three times per year","sampling_procedure":"No sampling, covers total population in demographic surveillance area","coll_mode":"Face-to-face [f2f]","research_instrument":"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.\n\nhttp:\/\/www.who.int\/healthinfo\/statistics\/verbalautopsystandards\/en\/index1.html","coll_situation":"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.","weight":"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].\n\nEach 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.\n\nTable 1:\n<pre>Age Group      INDEPTH 2013 standard\n                  Male      Female\n0-28 days        0.11%       0.10%\n1-11 months      1.49%       1.38%\n1-4 years        6.01%       5.57%\n5-14 years      13.76%      12.57%\n15-49 years     22.54%      23.50%\n50-64 years      3.87%       4.36%\n65+ years        2.22%       2.52%<\/pre>\n\n1. 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.","cleaning_operations":"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\"","method_notes":"All records have been anaonymised by associating a randomly generated serial number with each case. To facilitate linkage to other data sets released on the INDEPTH Data Repository a linkage file can be requested from the investigators."}},"data_access":{"dataset_availability":{"access_place":"INDEPTH Data Repository","access_place_uri":"http:\/\/www.indepth-ishare.org\/index.php\/catalog\/48","original_archive":"INDEPTH Data Repository\nhttp:\/\/www.indepth-ishare.org\/index.php\/catalog\/48\nCose: None"},"dataset_use":{"contact":[{"name":"Osman Sankoh","affiliation":"INDEPTH Network","email":"osman.sankoh@indepth-network.org","uri":""},{"name":"Kobus Herbst","affiliation":"INDEPTH Network","email":"kherbst@africacentre.ac.za","uri":""}],"cit_req":"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>","conditions":"This data is made available for licensed access under the following conditions: \n\n1. Data and other material provided by INDEPTH will not be redistributed or sold to other individuals, institutions or organisations without INDEPTH's written agreement. \n\n2. 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.  \n\n3. 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. \n\n4. No attempt will be made to produce links between datasets provided by INDEPTH or between INDEPTH data and other datasets that could identify individuals. \n\n5. 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. \n\n6. An electronic copy of all publications based on the requested data will be sent to INDEPTH. \n\n7. 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.\n\n8. Any published use of the data must cite the dataset as specified under the citation requirements.","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."}}},"data_files":[{"file_id":"F1","file_name":"CODA_2013_v7_Anonymised","description":"INDEPTH NETWORK CAUSE-SPECIFIC MORTALITY - RELEASE 2014","case_count":"176834","var_count":"17","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null}],"variables":[{"vid":"V1","name":"id","file_id":"F1","var_dcml":"0","var_intrvl":"discrete","var_start_pos":"1","var_end_pos":"5","var_width":"5","var_rec_seg_no":"1","labl":"Anonymised individual 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