Names, distributions and status of Queensland plants, algae, fungi, lichens and cyanobacteria, based on the Queensland Herbarium database 'Herbrecs'. Please refer to Flora census web page page for further information. See also the Botanical Dictionary for use with spell checkers.

Abstract

The 2019 Sierra Leone Demographic and Health Survey (2019 SLDHS) is a nationwide survey with a nationally representative sample of approximately 13,872 selected households. All women age 15-49 who are usual household members or who spent the night before the survey in the selected households were eligible for individual interviews.

The primary objective of the 2019 SLDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey collected information on fertility, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and children, maternal and child health, adult and childhood mortality, women’s empowerment, domestic violence, female genital cutting, prevalence and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), and other health-related issues such as smoking.

The information collected through the 2019 SLDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-59, and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019 SLDHS is the Population and Housing Census of the Republic of Sierra Leone, which was conducted in 2015 by Statistics Sierra Leone. Administratively, Sierra Leone is divided into provinces. Each province is subdivided into districts, each district is further divided into chiefdoms/census wards, and each chiefdom/census ward is divided into sections. During the 2015 Population and Housing Census, each locality was subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster for the 2019 SLDHS, is defined based on EAs from the 2015 EA census frame. The 2015 Population and Housing Census provided the list of EAs that served as a foundation to estimate the number of households and distinguish EAs as urban or rural for the survey sample frame.

The sample for the 2019 SLDHS was a stratified sample selected in two stages. Stratification was achieved by separating each district into urban and rural areas. In total, 31 sampling strata were created. Samples were selected independently in every stratum via a two-stage selection process. Implicit stratifications were achieved at each of the lower administrative levels by sorting the sampling frame before sample selection according to administrative order and by using probability-proportional-to-size selection during the first sampling stage.

In the first stage, 578 EAs were selected with probability proportional to EA size. EA size was the number of households residing in the EA. A household listing operation was carried out in all selected EAs, and the resulting lists of households served as a sampling frame for the selection of households in the second stage. In the second stage’s selection, a fixed number of 24 households were selected in every cluster through equal probability systematic sampling, resulting in a total sample size of approximately 13,872 selected households. The household listing was carried out using tablets, and random selection of households was carried out through computer programming. The survey interviewers interviewed only the pre-selected households. To prevent bias, no replacements and no changes of the pre-selected households were allowed in the implementing stages.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019 SLDHS: The Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Fieldworker Questionnaire. The questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Sierra Leone. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. The survey protocol was reviewed and approved by the Sierra Leone Ethics and Scientific Review Committee and the ICF Institutional Review Board. All questionnaires were finalised in English, and the 2019 SLDHS used computer-assisted personal interviewing (CAPI) for data collection.

Cleaning operations

The processing of the 2019 SLDHS data began almost as soon as the fieldwork started. As data collection was completed in each cluster, all electronic data files were transferred via the IFSS to the Stats SL central office in Freetown. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams received alerts on any inconsistencies and errors. Secondary editing, carried out in the central office, involved resolving inconsistencies and coding open-ended questions. The Stats SL data processor coordinated the exercise at the central office. The biomarker paper questionnaires were compared with electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro Systems software package. Concurrent processing of the data offered a distinct advantage because it maximised the likelihood of the data being error-free and accurate. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in mid-October 2019.

Response rate

A total of 13,793 households were selected for the sample, of which 13,602 were occupied. Of the occupied households, 13,399 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 16,099 women age 15-49 were identified for individual interviews; interviews were completed with 15,574 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 7,429 men age 15-59 were identified, and 7,197 were successfully interviewed, yielding a response rate of 97%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019 Sierra Leone Demographic and Health Survey (SLDHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019 SLDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling errors are usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019 SLDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programmes developed by ICF. These programmes use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Completeness of reporting
• Births by calendar years
• Reporting of age at death in days
• Reporting of age at death in months
• Standardisation exercise results from anthropometry training
• Height measurements from random subsample of measured children
• Sibship size and sex ratio of siblings
• Pregnancy-related mortality trends
• Completeness of information on siblings

See details of the data quality tables in Appendix C of the final

Abstract

The National Agricultural Survey 2008 (NAS 2008) was designed to provide a picture with reliable and updated agriculture sector figures, in order to serve as a baseline based on the facts and to set up development strategies that are most appropriate for the rural sector. This will steer progress towards the goals of Vision 2020, while having the fittest tools for measuring, monitoring and evaluation. Indeed in the context of Vision 2020 adopted by the highest authorities of the country, the transformation of agriculture is one of the pillars of that vision. The 2008 National Agricultural Survey (NAS) of Rwanda was undertaken from September 2007 to August 2008. As a result of the 1994 genocide, lives were lost, people were displaced or exiled. Without accurate measurements, it was not possible to evaluate objectively the performance of the agricultural sector and to know the real contribution of agriculture to the economy. Prior to the 2008 National Agricultural Survey, annual agricultural production was estimated using projections of an agricultural survey conducted in 1990, a methodology that was both inaccurate and unreliable.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The unit of observation was the agricultural household. This was defined as the household where at least one member was engaged in any of the following; agricultural activities, livestock, fisheries, forestry or bee-keeping. A form for listing was used to identify this type of household. The unit of analysis was the holding (large-farm) or agricultural household. The agriculture sample frame consists of all agricultural households residing in the enumeration area.

Kind of data

Census/enumeration data [cen]

Sampling procedure

i. Frame The sampling frame and cartography for the National Agricultural Survey 2008 came from the 2002 General Census of Population and Housing (RGPH). The RGPH included an agricultural module that was administered to all households to identify the agricultural households. Complete or sample enumeration methods The 2008 National Agricultural Survey (NAS 2008) covered a sample of 10,080 agricultural households spread out in all 30 Districts and the data are representative at the District level.

ii. Sample Design The sample was a two-stage stratified sample design. The number of agricultural households identified in the 2002 General Census of Population and Housing was used as a measure of the size of the enumeration area (EAs). In order to have reliable survey estimates at the District level, the first stage of stratification was down at the District level. The Districts of Kigali City (Nyarugenge, Gasabo, Kicukiro) were grouped into one stratum because of the small number of agricultural EA’s in each District. At the first stage of stratification, there were 28 strata. The second stage of stratification was to further divide the EAs in each District into the particular bio-climatic zone in which they were situated. Thus, each agricultural EA was classified into one of the Rwanda’s ten agro-climatic zones. The analysis of the agricultural sample frame showed that most Districts (19) had two agro-climatic zones, six Districts had three agro-climatic zones, two (Musanze and Nyamasheke) had four zones and three Districts were in a single-agro climatic zone. In consideration of the financial and operational constraints, and in order to have reliable estimates at district level, the methodologists recommended the selection of 840 EAs as the primary sampling units (PSU’s). The PSU’s were geographical areas with clearly identifiable boundaries so that an enumerator could conduct the listing of households during a fixed period of time. The sample EAs were drawn using probability proportional to size (PPS).The size of each PSU was the number of households. The sample was then divided into 4 sub-samples (replicates) of 210 EA’s each that could be used for post-census surveys. Households were listed within sample EA’s in order to establish an up-to-date list of households in the EA. The listing led to the identification of agricultural households - the secondary sampling units. These lists of agricultural households allowed for the random selection of 15 agricultural households by EA with equal probability of selection. Among these 15 households, 12 participated in interviews and 3 served as replacements should a selected household be a no-contact or a refusal. In the second stage, 12 households were interviewed in each sample EA. For the National Agricultural Survey 2008, there were a total of 10,080 households sampled.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were 18 separate Forms or Questionnaires. The Census of Agriculture collected all the core data as recommended by the FAO. The forms used were:

FORM 1: Characteristics of members of agricultural household FORM 2.1: Identification of blocks of the holding FORM 2.2: Sketch of basic blocks FORM 2.3: Data of the field FORM 2.4: List of cultures FORM 3: Purchase of agricultural inputs FORM 4.1: Register for daily harvest FORM 4.2: Summary of monthly record for daily harvest FORM 5.1: Inventory of livestock FORM 5.2: Flux and animal production FORM 6: Squares yield FORM 7.1: Register for daily fishery products FORM 7.2: Fishing activities FORM 8: Activities of beekeeping FORM 9: Activities of forestry FORM 10: Activities of horticulture FORM 11: Storage of harvest FORM 12: Nutrition and household food

All questionnaires are attached to the external materials section.

Cleaning operations

i. Data Entry Upon the closing of fieldwork of season 2008, a large volume of data was available for entry. This required a consistent supply and a significant number of staff input to recruit and employ. Unfortunately, organizational and financial difficulties arose and led to a late start of data entry. For data entry operations, a computer program was developed using a CSPro statistical software application with a questionnaire on each sheet. A training session was organized on this data entry program and on the nature and extent of work to do. In total, this operation mobilized 184 data entry clerks, 10 controllers, 3 checkers, 3 supervisors of coding and 92 computers. A first team of data entry clerks, controllers and checkers worked in the morning and was be relayed by a second team to work in the evening.

ii. Data cleaning and processing A computer statistician consultant was recruited for the cleaning work and data processing for NAS 2008. The methodology followed in cleaning and processing the data is contained in the document «Plan méthodologique pour l’apurement et le traitement des données» formulated by the consultant. The consultant had to monitor compliance with the codification of collection sheets and make the necessary corrections.

iii. Data analysis An international consultant has been recruited to carry out the analysis of the NAS 2008. The analysis covered the demographic and social characteristics of agricultural farmers, farms characteristics, agricultural practices and crop production, livestock practices and production, fishery, aquaculture and beekeeping practices, forestry practices and income, as well as food stocks and nutrition of agricultural households.

Data appraisal

The 2008 National Agricultural Survey results were compared to other pre-existing routine data (according to their availability and reliability). The comparable data was mainly from the Ministry of Agriculture - particularly data on agricultural production, yield and area, livestock numbers, and production. There was also some data on, for example, coffee and tea from the “Office des Cultures Industrielles du Rwanda”, that were in line with that from the NAS 2008 (with discrepancies explained by exclusions and differences noticed in the methodology).

Names, distributions and status of Queensland plants, algae, fungi, lichens and cyanobacteria, based on the Queensland Herbarium database 'Herbrecs'. Please refer to Flora census web page page for further information. See also the Botanical Dictionary for use with spell checkers.

Names, distributions and status of Queensland plants, algae, fungi, lichens and cyanobacteria, based on the Queensland Herbarium database 'Herbrecs'. Please refer to Flora census web page page for further information. See also the Botanical Dictionary for use with spell checkers.