{"doc_desc":{"title":"TZA_2003_ANSC_v01_M","idno":"DDI-TZA-2003-ANSC-v01-M-OCGS","producers":[{"name":"The Office of  Chief Government Statistician","abbreviation":"OCGS","affiliation":"Ministry of Finance and Economy Affairs","role":"Documentation of the study"}],"prod_date":"2023-10-13","version_statement":{"version":"Version 1.0"}},"study_desc":{"title_statement":{"idno":"TZA-2002-2003-ANSC-v01-M","title":"Agriculture National Sample Census 2002\/2003","sub_title":"Volume VIII: Livestock Sector - Zanzibar Report","alt_title":"ANSC 2002\/2003"},"authoring_entity":[{"name":"The Office of  Chief Government Statistician","affiliation":"Ministry of Finance and Economic Affairs "},{"name":"National Bureau of Statistics","affiliation":"Ministry of Planning and Empowerment"},{"name":"Ministry of Agriculture, Natural Resources, Environment and Cooperatives","affiliation":"Revolutionary Government of Zanzibar "}],"oth_id":[{"name":"Dr.G.M. Naiman","affiliation":"University of Dar es Salaam","email":"","role":"Sampling design and methodology"},{"name":"Regional Agricultural Development Officers","affiliation":"Ministry of Agriculture Natural Resources, Environment and Cooperatives","email":"","role":"implementation of census activities"},{"name":"District Agricultural Development Officers","affiliation":"Ministry of Agriculture Natural Resources, Environment and Cooperatives","email":"","role":"implementation of census activities"},{"name":"Local Government Officials","affiliation":"Local Government ","email":"","role":"implementation of census activities"}],"production_statement":{"producers":[{"name":"Food and Agriculture Organisation","affiliation":"United Nation","role":"Technical assistance"},{"name":"Scotts Agriculture Consultancy","affiliation":"","role":"Technical assistance"},{"name":"Ultek Laurence Gold Consultants","affiliation":"","role":"Technical assistance"}],"copyright":"(c) 2002\/2003,The Office of  Chief Government Statistician","funding_agencies":[{"name":"United Nations Development Programme","abbreviation":"UNDP","role":"Financial Support"},{"name":"Eurpean Union","abbreviation":"UN","role":"Financial Support"},{"name":"Government of Japan","abbreviation":"GJ","role":"Financial Support"},{"name":"Revolutionary Government of Zanzibar","abbreviation":"RGoZ","role":"Financial Support"},{"name":"Department for International Development","abbreviation":"DFID","role":"Financial Support"},{"name":"Japan International Cooperation Agency","abbreviation":"JICA","role":"Financial Support"}]},"distribution_statement":{"contact":[{"name":"Head of data Management Division","affiliation":"The Office of Chief Government Statistician","email":"abdullah.makame@ocgs.go.tz","uri":"www.ocgs.go.tz"}]},"series_statement":{"series_name":"Agricultural Census [ag\/census]","series_info":"The 2002-2003 National Sample Census of Agriculture is the first comprehensive Sample Census of Agriculture undertaken in Zanzibar."},"version_statement":{"version":"- v2.1:  Edited, anonymous dataset for public distribution.","version_date":"2006-05"},"study_info":{"abstract":"NATIONAL SAMPLE CENSUS OF AGRICULTURE (2002\/2003)-LIVESTOCK SECTOR\n\nThe analysis and data contained in this report provide description of the state of the livestock sector in Zanzibar for the agriculture year 1st October 2002 to 30th September 2003. The analysis and tabulation are based on small holders disaggregated and compared to district level.During the reference period there were 36,445 livestock keeping households which represent 38 percent of the total small holder agriculture households. \n\nAs of 1st October 2003 there were 215,802 heads of major livestock. The population of cattle was 162,643 followed by goats (52,324), sheep (300) and pigs (535). Most of the livestock keeping households have both cattle and goats. An estimated 91 percent of the livestock keepers raise cattle, 26 percent raise goats while 0.2 percent keep sheep and only 0.1 percent manage pigs. The average herd size kept by households for different types of livestock are five heads for cattle keeping households, six in the case of goats, four for sheep and 10 in the case of pigs. Micheweni, Central, West and Wete districts are important in livestock enterprise but for Micheweni in particular, its flock is comprised almost entirely of indigenous species. Most of the livestock of improved breeds are in West and Central districts. Chicken are the most important poultry and their number on the reference date was 1,063,791 kept by 66,736 households. The average number of chicken kept by the households is thus 16. \n\nZanzibar has the highest density of chicken in Tanzania. Mkoani has the highest population of indigenous chicken but almost no improved chicken whereas West and Central district have comparatively good number of exotic chicken which have led to these two districts to be leading in having more chicken than other districts. Compared to 1992\/93 livestock census, the population of major livestock types is increasing with time except in case of sheep and donkeys. The average growth rate for indigenous cattle is 3.6 percent per annum, 7.6 percent for improved cattle, 1.6 percent for goat, -7.6 percent for sheep and an incredible average growth rate of 23.3 percent per annum has been realized for pigs. The average annual growth rate for indigenous chicken is 4 percent, 10.3 percent for layers while the population of broilers has been decreasing at the rate of -5.5 percent per annum.\nIndigenous livestock species are very dominant and account 95 percent for cattle, 99.5 percent for goats, 100 percent \nsheep and 89 percent chicken. \n\nMilk is obtained from cattle and goats where goat's contribution is less than one percent. Due to high proportion of improved cattle in West and Central districts, each of the districts produce more milk than Micheweni District which has a higher number of cattle but almost all are of indigenous species. About 95 percent of the households that produced milk sold some, mostly to neighbours and milk vendors at an average farm gate price of Tsh 250 per litre. The households sell about 66 percent of the milk they produce. \n\nThere is some contribution of livestock to crop production in the form of improving soil fertility and structure by using farmyard manure but livestock are almost not used for soil cultivation. Farmyard manure was applied on about 8887ha. The districts where the manure is mostly used are West, Central and MicheweniThe diseases that affect a large number of livestock are tick-borne, mostly East Coast Fever to cattle. Helmenthiosis infect both cattle and goats but due to improved management in pigs, the condition was not reported in piggeries. Contagious Caprine Pleuro-pneumonia (CCP) has affected goats in some districts in Unguja but has not been \nreported in any district of Pemba. Contagious Bovine Pleuro-pneumonia and Trypanasomiasis have not been recorded anywhere in Zanzibar. \n\nThe distance from livestock keeper's households to livestock infrastructures for services is about 10 km. or more for more than 50 percent of the households. The main source of extension services is the government (82 percent) followed by development projects\/NGOs (5 percent). There was no Fish Farming reported during the time of this census.","coll_dates":[{"start":"2003-10-30","end":"2003-11-10","cycle":"10 days"}],"nation":[{"name":"Zanzibar,Tanzania","abbreviation":"TZA"}],"geog_coverage":"Zanzibar\nUrban and Rural\nRegions\nIt covered nine out of 10 districts(Mjini district was not included)","analysis_unit":"Agriculture Households for both Household and  Individual level","universe":"All Household members aged 15 years and above","data_kind":"Sample survey data [ssd]","notes":"The  scope of Agriculture national sample census includes:\n-Annual crop and vegetable production\n-Cattle\n-Crop extension services\n-Goat\n-Livestock\n-Marketing problem\n-Milk production\n-Other data\n-Pig\n-Sheep\n-Subsistence and non Subsistence\n-Use of credit of Agriculture purposes"},"method":{"data_collection":{"data_collectors":[{"name":"The Office of Chief Government Statistician","abbreviation":"OCGS","affiliation":"Ministry of Finance and Economic Affairs"}],"sampling_procedure":"A sample was extracted from the Zanzibar National Master Sample (NMS) developed with technical assistance of  Dr. G.M. Naiman from the University of Dar es Salaam.The sample consisted of 317 EA's spread over nine districts. These EA's were drawn from the NMS developed by the OCGS to serve as a national framework for different sample censuses and surveys to be conducted in Zanzibar.\nA stratified two stage sample was established. The numbers of EAs were selected at the first stage with a probability proportional to the number of households in each EA. At the second stage, 15 farming households were selected from each EA using \nsystematic random sampling.","coll_mode":["Face-to-face [f2f]"],"research_instrument":"Listing questionaire was used to list all Households inside the enumeration areas(EA)\nThree different questionnaires were used to collect data on agriculture and related aspects. These were:- \n- Small scale farm questionnaire \n- Community questionnaire \n- Large scale farm questionnaire","coll_situation":"Questionnaire Design and Other Census Instruments \nThe questionnaire was designed following users meetings to ensure that the questions asked were in line with the \nusers data needs. Several features were incorporated into the design of the questionnaire to increase the accuracy of \nthe data. \n-Where feasible all variables were extensively coded to reduce post enumeration coding error. \n- The definition for each section were printed on the opposite page so that the enumerator could easily \nrefer to the instructions whilst interviewing the farmer \n- The responses to all questions were placed in boxes printed on the questionnaire, with one box per \ncharacter. This feature made it possible to use scanning and Intelligent Character Recognition (ICR) \ntechnologies for data entry. \n- Skip pattern were used to reduce unnecessary and incorrect coding of section which do not apply to \nthe respondent. \nEach section was clearly numbered, which facilitated the use of skip patterns and provided a reference for data \ntype coding for the programming of CSPro, SPSS and dissemination applications. \nThree other instruments were used: \n- Village Listing Forms were used for listing households in the village and from this list a systematic \nsample of 15 agricultural households were selected \n- A training manual which was used by the trainers for the cascade\/pyramid training of supervisors and \nenumerators. \n- Enumerator Instruction Manual was used as reference material\nField Pre-testing of the Census Instruments\nThe Small Scale Farmer Questionnaire was pre-tested in different areas in both Unguja and Pemba. The villages ofBambi and Ndijani in South Region Unguja, Kinyasini and Matemwe in North Unguja, Chakechake and Micheweniin Pemba were used as pilot areas to test the questionnaire. \n\nTraining of Trainers, Supervisors and Enumerators\nTraining Programme for the census was prepared and carried out prior to the actual field work. Four participantsfrom Zanzibar attended the national training of trainers' course in Dodoma. The idea was to have a uniformity oftraining on the modality of filling in questionnaire between Mainland and Zanzibar.A training program was developed and four centers were used to impart knowledge and skills of filling in thequestionnaires and conducting the interviews. Jambiani Centre was used as venue for training of regional agriculturedevelopment officers (RADOs), district agriculture development officers (DADOs) and statistics officers, Mahondaand Amani were used as training centers for field enumerators and supervisors in Unguja and Madungu for fieldenumerators and supervisors for Pemba. Emphasis was placed on training the enumerators and supervisors inconsistency checks. Tests were given to the enumerators and supervisors and those who did well were selected for the actual field work.\n\nData Collection\nData collection activities started on 30th, October 2003 and lasted for 10 days for both Unguja and Pemba. However,in some areas data collection was prolonged up to a month. The data collection methods used during the censusconsisted of interviewing heads of households and an elaborate field organization was set up to increase the accuracyof the collected data. The enumeration was done by staff from of the Ministry of Agriculture, Natural Resources,Environment and Cooperatives. Supervision was provided by senior officers of the same ministry and the Office ofChief Government Statistician. 158 enumerators were used and additional five percent were held as reserves in case of drop outs during the enumeration exercise.","act_min":"Supervision was provided by senior officers of the same ministry and the Office ofChief Government Statistician. 158 enumerators were used and additional five percent were held as reserves in case of drop outs during the enumeration exercise.","weight":"Not included in this report","cleaning_operations":"Enumerators were trained to probe the respondents until they were satisfied with the responses given before they recorded in the survey questionnaires. The first check of the filed questionnaires was done by enumerators in the field and then by field supervisors. The second check was done by district supervisor (DADOS) who signed the questionnaire and handed them over to regional supervisors for further checking.National supervisors then worked on all questionnaires focusing on consistency checking and when inconsistencies\nwere found the concerned enumerators were instructed to go back to the respondent to get the correct data.","method_notes":"CSPro data base was used for manual data entry, data capturing and cleaning. The method was adopted due to the relatively small number of questionnaires compared to the Mainland where scanning and ICR data capture technology were used. Interactive validation program was incorporated to counter check the validity of entered data. Manual data cleaning was carried out before the actual data entry; this exercise was meant to assess the correctness of identifications in each questionnaire and other inconsistencies. However, latter the data was taken to the mainland where the process of ICR was done after the scanning of the Zanzibar questionnaires.\n \nData Structure Formatting \nFollowing scanning, visual basics was used to harmonise with the manual entered data. The programme automatically checked and changed the number of digits for each variable, the report type code, the number of questionnaires in the aenumeration area, the consistency of the area ID and saved the data of one area in a file named after the area code. \n\nBatch Validation \nA batch validation programme was developed in order to identify inconsistencies within the questionnaire. CSPro data base was used for manual data entry, data capturing and cleaning. The method was adopted due to the relatively small number of questionnaires compared to the Mainland where scanning and ICR data capture technology were used. Interactive validation program was incorporated to counter check the validity of entered data. Manual data cleaning was carried out before the actual data entry; this exercise was meant to assess the correctness of identifications in each questionnaire and other inconsistencies. After the long process of data cleaning, the tabulation were prepared based on the pre-designed tabulation plan. \n\nTabulation \nStatistical Package for Social Science (SPSS) was used to produce the Census tabulations and Microsoft Excel was  used to organise the tables and compute the additional indicators. Excel was also used to produce charts while ArcView  and Freehand was used for the maps. \n\nAnalysis and Report Preparation \nThe analysis on this report focuses on district comparisons, time series and production estimates. Microsoft Excel was used to produce charts; ArcView and Freehand were used for maps, whereas Microsoft Word was used to compile the report."},"analysis_info":{"response_rate":"Not stated in this report","sampling_error_estimates":"Not stated"}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"Confidentiality of respondent guaranteed under Statistical Act  No. 9 of  2007\nThe Chief Government Statistician may disclose information in the form ofindividual statistical records solely for bona fide research or statistical\npurposes provided that:-\n(a) all identification such as name and address has been removed;\n(b) the information is disclosed in a manner that is not likely to enable the identification of the particular person or undertaking or business to which it relates.","required":"yes","form_no":"","uri":""}],"contact":[{"name":"Chief Government Statistician","affiliation":"The Office of Chief Government Statistician","email":"zanstat@ocgs.go.tz","uri":"www.ocgs.go.tz"}],"cit_req":"\"The Office of Chief Government Statistician,Agriculture National Sample Census 2002\/2003(ANSC 2002\/2003),Version 2.1 of the public use dataset(March 2004),provided by the National Data Archive. www.ocgs.go.tz\"","conditions":"The Office of Chief Government Statistician considered three levels of accessibility:\n1) Public use files, accessible by all\n2) Licensed datasets, accessible under certain conditions\n3) Datasets only accessible on location, for certain datasets\nAny person or organization to whom any statistical records are disclosed shall: -\n(a) not attempt to identify any particular person or undertaking or business;\n(b) use the information for research or statistical purposes only;\n(c) not disclose the information to any other person or organization;","disclaimer":"\"The user of the data acknowledges that,The Office of Chief Government Statistician is the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses\"."}}},"schematype":"survey"}