This report and dataset describe one area of intensive Israeli military earthworks activity subsequent to the end of the ceasefire between Israel and Hamas on March 18, 2025. It focuses on the surroundings of a compound of 81,000 m2 (81 dunam) in the very northwest corner of the Gaza strip (marked as object 1 in the inset box in Figure 1 below). The activity in southern Gaza—including this area in particular —are significant in light of the declared new phase of Israeli army efforts following after the renewal of full-scale conflict on March 18. As described here, this phase new phase of the war, as sweepingly outlined by Israeli government officials, including intensive ground, air, and sea attacks, the relocations of populations to the southern part of the Gaza Strip, and more permanent occupation by Israeli forces, as described below. The rapid progress and the high level of clearance and leveling, the new access road, and the strategic positioning of this compound all suggest it is intended to take on a significant role in the intended next phase, possibly related to aid distribution and population sorting and separation. Given the considerable chaos and churn in overarching development and Israel’s announcements, it is important to examine actual developments on the ground for a more solid sense of Israel’s intentions and commitments. This is the intention of the maps and data in this document and accompanying files, which will be updated and augmented as developments warrant. This continues a series of reports and deposits of geospatial data related to Israeli military activity in the Gaza Strip providing up-to-date spatial inputs requested by international humanitarian NGOs, Gazan residents, and the media.

Abstract

The Agricultural Census aims in general to establish an updated, detailed and accurate holdings database to assist in planning and policy making at all levels related to the agricultural sector. It also aims in specific to provide data on the structure of agriculture, especially for small administrative and geographical units, rare items, and to enable detailed cross-tabulations, and to provide data that can be used as a benchmark for reconciliation of current agricultural statistics; and for setting estimates for subsequent years, in addition to provide frames for agricultural sampling surveys.

Geographic coverage

The census also covered all geographical levels in the West Bank and Gaza Strip, so that: 1. Implementation of a comprehensive listing in Gaza Strip that enumeration areas represent more than 5% of households that practice agricultural activity, according to the Population, Housing and Establishments Census, 2017 data. 2. Visiting the households that practiced agricultural activity according to data of Population, Housing and Establishments Census, 2017 in the enumerated areas, where the percentage of households that practiced an agricultural activity is 1-4%. 3. Implementation of a comprehensive listing in the West Bank for all localities except camps and city centers in the following governorates (Nablus, Ramallah & Al-Bireh, Hebron and J2 in Jerusalem Governorate). 4. Implementation of a comprehensive listing in the enumeration areas of camps and city centers in the following governorates (Nablus, Ramallah, Al-Bireh, Hebron and J2 of Jerusalem Governorate), for households that practiced agricultural activity according to data of Population, Housing and Establishments Census 2017, more than 5%, and visiting the households that practiced agricultural activity according to data of Population, Housing and Establishments Census 2017 in the enumerated areas, where the percentage of households that practiced an agricultural activity is 1-4% in the same locality mentioned above. 5. About Jerusalem J1, a different methodology is applied in two phases. In the first phase, research and investigation are carried out in cooperation with responsible and dignitaries in Jerusalem J1 on agricultural holdings and holders, and in the second phase, enumeration of the holdings that were monitored in the first phase.

Analysis unit

Agricultural Holding

Universe

Includes agricultural holdings in Palestine in 2021

Kind of data

Census/enumeration data [cen]

Sampling procedure

The frame of the Agriculture Census includes a complete record of households and non-household agricultural holdings, where all households are enumerated and the household agricultural holdings are identified, in addition to a list of non-households holdings that is obtained by listing all buildings as well as a list from the Ministry of Agriculture which includes cooperative societies/charity societies, companies, and government and private holdings…etc.

The census also covered all geographical levels in the West Bank and Gaza Strip, so that: 1. Implementation of a comprehensive listing in Gaza Strip that enumeration areas represent more than 5% of households that practice agricultural activity, according to the Population, Housing and Establishments Census, 2017 data. 2. Visiting the households that practiced agricultural activity according to data of Population, Housing and Establishments Census, 2017 in the enumerated areas, where the percentage of households that practiced an agricultural activity is 1-4%. 3. Implementation of a comprehensive listing in the West Bank for all localities except camps and city centers in the following governorates (Nablus, Ramallah & Al-Bireh, Hebron and J2 in Jerusalem Governorate). 4. Implementation of a comprehensive listing in the enumeration areas of camps and city centers in the following governorates (Nablus, Ramallah, Al-Bireh, Hebron and J2 of Jerusalem Governorate), for households that practiced agricultural activity according to data of Population, Housing and Establishments Census 2017, more than 5%, and visiting the households that practiced agricultural activity according to data of Population, Housing and Establishments Census 2017 in the enumerated areas, where the percentage of households that practiced an agricultural activity is 1-4% in the same locality mentioned above. 5. About Jerusalem J1, a different methodology is applied in two phases. In the first phase, research and investigation are carried out in cooperation with responsible and dignitaries in Jerusalem J1 on agricultural holdings and holders, and in the second phase, enumeration of the holdings that were monitored in the first phase.

Sampling deviation

Not applicable

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Computerized program

Cleaning operations

Post enumeration data processing phase was limited to final examination and cleaning of Agricultural Census databases, with documentation of examinations on all topics of Agricultural Census 2021 questions. Data processing phase focused on the following: 1. Checking the allowed transfers and values. 2. Checking the consistency between different questions of the census questionnaire based on logical relationships. 3. Checking on the basis of relations between certain questions so that a list of non-identical cases was extracted, reviewed and identified the source of the error case by case, and if such errors were immediately modified and corrected based on the source of the error3. Checking on the basis of relations between certain questions so that a list of non-identical cases was extracted, reviewed and identified the source of the error case by case, and if such errors were immediately modified and corrected based on the source of the error.

Response rate

Not Applicable.

Sampling error estimates

The sampling errors occur during the sample-based surveys but not in censuses as it is a comprehensive inventory of all agricultural holdings. These errors are easy to measure with the error point estimate also, since it is considered as an error in the sample.

Data appraisal

The non-sampling errors occur at any stage during the implementation of censuses and surveys. Therefore, it is necessary to provide for a data quality control system to ensure maximum accuracy. Many of these stages were used during the agriculture census planning and implementation where are-interview was carried out as follows:

• There are two models that were used to collect data and were uploaded to tablets. The first model is to enumerate households in all enumeration areas; in which the percentage of households that practiced an agricultural activity (according to the data of the Population, Housing and Establishments Census, 2017) is 5% or more, and the second model was used if the household had agricultural holdings.

• The enumerator visited Palestinian households in the enumeration areas in which the percentage of households that practiced agricultural activity (according to the data of the Population, Housing and Establishments Census, 2017) is less than 5%, so that the inventory model and the model prepared for agricultural holdings were if the tenure conditions were met.

State of Palestine (West Bank and Gaza) Crude Death Rate: per 1000 Population: Gaza Strip data was reported at 3.500 NA in 2018. This records an increase from the previous number of 3.400 NA for 2017. State of Palestine (West Bank and Gaza) Crude Death Rate: per 1000 Population: Gaza Strip data is updated yearly, averaging 3.950 NA from Dec 1997 (Median) to 2018, with 18 observations. The data reached an all-time high of 4.700 NA in 1997 and a record low of 3.300 NA in 2016. State of Palestine (West Bank and Gaza) Crude Death Rate: per 1000 Population: Gaza Strip data remains active status in CEIC and is reported by Palestinian Central Bureau of Statistics. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.G002: Vital Statistics.

Abstract

The Consumer price surveys primarily provide the following: Data on CPI in Palestine covering the West Bank, Gaza Strip and Jerusalem J1 for major and sub groups of expenditure. Statistics needed for decision-makers, planners and those who are interested in the national economy. Contribution to the preparation of quarterly and annual national accounts data.

Consumer Prices and indices are used for a wide range of purposes, the most important of which are as follows: Adjustment of wages, government subsidies and social security benefits to compensate in part or in full for the changes in living costs. To provide an index to measure the price inflation of the entire household sector, which is used to eliminate the inflation impact of the components of the final consumption expenditure of households in national accounts and to dispose of the impact of price changes from income and national groups. Price index numbers are widely used to measure inflation rates and economic recession. Price indices are used by the public as a guide for the family with regard to its budget and its constituent items. Price indices are used to monitor changes in the prices of the goods traded in the market and the consequent position of price trends, market conditions and living costs. However, the price index does not reflect other factors affecting the cost of living, e.g. the quality and quantity of purchased goods. Therefore, it is only one of many indicators used to assess living costs. It is used as a direct method to identify the purchasing power of money, where the purchasing power of money is inversely proportional to the price index.

Geographic coverage

Palestine West Bank Gaza Strip Jerusalem

Analysis unit

The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

Universe

The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

Kind of data

Sample survey data [ssd]

Sampling procedure

A non-probability purposive sample of sources from which the prices of different goods and services are collected was updated based on the establishment census 2017, in a manner that achieves full coverage of all goods and services that fall within the Palestinian consumer system. These sources were selected based on the availability of the goods within them. It is worth mentioning that the sample of sources was selected from the main cities inside Palestine: Jenin, Tulkarm, Nablus, Qalqiliya, Ramallah, Al-Bireh, Jericho, Jerusalem, Bethlehem, Hebron, Gaza, Jabalia, Dier Al-Balah, Nusseirat, Khan Yunis and Rafah. The selection of these sources was considered to be representative of the variation that can occur in the prices collected from the various sources. The number of goods and services included in the CPI is approximately 730 commodities, whose prices were collected from 3,200 sources. (COICOP) classification is used for consumer data as recommended by the United Nations System of National Accounts (SNA-2008).

Sampling deviation

Not apply

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

A tablet-supported electronic form was designed for price surveys to be used by the field teams in collecting data from different governorates, with the exception of Jerusalem J1. The electronic form is supported with GIS, and GPS mapping technique that allow the field workers to locate the outlets exactly on the map and the administrative staff to manage the field remotely. The electronic questionnaire is divided into a number of screens, namely: First screen: shows the metadata for the data source, governorate name, governorate code, source code, source name, full source address, and phone number. Second screen: shows the source interview result, which is either completed, temporarily paused or permanently closed. It also shows the change activity as incomplete or rejected with the explanation for the reason of rejection. Third screen: shows the item code, item name, item unit, item price, product availability, and reason for unavailability. Fourth screen: checks the price data of the related source and verifies their validity through the auditing rules, which was designed specifically for the price programs. Fifth screen: saves and sends data through (VPN-Connection) and (WI-FI technology).

In case of the Jerusalem J1 Governorate, a paper form has been designed to collect the price data so that the form in the top part contains the metadata of the data source and in the lower section contains the price data for the source collected. After that, the data are entered into the price program database.

Cleaning operations

The price survey forms were already encoded by the project management depending on the specific international statistical classification of each survey. After the researcher collected the price data and sent them electronically, the data was reviewed and audited by the project management. Achievement reports were reviewed on a daily and weekly basis. Also, the detailed price reports at data source levels were checked and reviewed on a daily basis by the project management. If there were any notes, the researcher was consulted in order to verify the data and call the owner in order to correct or confirm the information.

At the end of the data collection process in all governorates, the data will be edited using the following process: Logical revision of prices by comparing the prices of goods and services with others from different sources and other governorates. Whenever a mistake is detected, it should be returned to the field for correction. Mathematical revision of the average prices for items in governorates and the general average in all governorates. Field revision of prices through selecting a sample of the prices collected from the items.

Response rate

Not apply

Sampling error estimates

The findings of the survey may be affected by sampling errors due to the use of samples in conducting the survey rather than total enumeration of the units of the target population, which increases the chances of variances between the actual values we expect to obtain from the data if we had conducted the survey using total enumeration. The computation of differences between the most important key goods showed that the variation of these goods differs due to the specialty of each survey. For example, for the CPI, the variation between its goods was very low, except in some cases such as banana, tomato, and cucumber goods that had a high coefficient of variation during 2019 due to the high oscillation in their prices. The variance of the key goods in the computed and disseminated CPI survey that was carried out on the Palestine level was for reasons related to sample design and variance calculation of different indicators since there was a difficulty in the dissemination of results by governorates due to lack of weights. Non-sampling errors are probable at all stages of data collection or data entry. Non-sampling errors include: Non-response errors: the selected sources demonstrated a significant cooperation with interviewers; so, there wasn't any case of non-response reported during 2019. Response errors (respondent), interviewing errors (interviewer), and data entry errors: to avoid these types of errors and reduce their effect to a minimum, project managers adopted a number of procedures, including the following: More than one visit was made to every source to explain the objectives of the survey and emphasize the confidentiality of the data. The visits to data sources contributed to empowering relations, cooperation, and the verification of data accuracy. Interviewer errors: a number of procedures were taken to ensure data accuracy throughout the process of field data compilation: Interviewers were selected based on educational qualification, competence, and assessment. Interviewers were trained theoretically and practically on the questionnaire. Meetings were held to remind interviewers of instructions. In addition, explanatory notes were supplied with the surveys. A number of procedures were taken to verify data quality and consistency and ensure data accuracy for the data collected by a questioner throughout processing and data entry (knowing that data collected through paper questionnaires did not exceed 5%): Data entry staff was selected from among specialists in computer programming and were fully trained on the entry programs. Data verification was carried out for 10% of the entered questionnaires to ensure that data entry staff had entered data correctly and in accordance with the provisions of the questionnaire. The result of the verification was consistent with the original data to a degree of 100%. The files of the entered data were received, examined, and reviewed by project managers before findings were extracted. Project managers carried out many checks on data logic and coherence, such as comparing the data of the current month with that of the previous month, and comparing the data of sources and between governorates. Data collected by tablet devices were checked for consistency and accuracy by applying rules at item level to be checked.

Data appraisal

Other technical procedures to improve data quality: Seasonal adjustment processes

Chiran Livera, head of emergency operations with the Canadian Red Cross, says the effort to provide humanitarian assistance to the affected population in the Gaza Strip and West Bank has been protracted, complex and traumatic for those in the field.

Abstract

The basic goal of this survey is to provide the necessary database for formulating national policies at various levels. It represents the contribution of the household sector to the Gross National Product (GNP). Household Surveys help as well in determining the incidence of poverty, and providing weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Generally, the Household Expenditure and Consumption Survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

The target population in the sample survey comprises all households living in the West Bank and Gaza Strip, excluding nomads and students.

Analysis unit

1- Household/families. 2- Individuals.

Universe

The survey covered a national sample of households and all permanently residing individuals in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame:

The target population in the survey sample comprises all households living in the West Bank and Gaza Strip, excluding nomads and students. The sample design is a stratified two-stage design for households selected to be interviewed. At the first stage a sample of cells (PSUs) was selected from PCBS master sample frame. At the second stage, a sample of households was selected after a complete household listing of the sampled cells.

Sample design:

Four levels of stratification have been made: 1. Stratification by District. 2. Stratification by place of residence, which comprises: (a) Municipalities (b) Villages (C) refugees camps 3. Stratification by locality size 4. Stratification by cell identification in that order

Sample size:

The sample size is about 3591 households allowing for non-response and related losses.

Target cluster size:

The target cluster size or the "sample-take" is the average number of households to be selected per PSU. In this survey, the sample take is around 10 households.

Detailed information/formulas on the sampling design are available in the user manual.

Sampling deviation

The standard errors for the main survey estimates were calculated to give the user an idea of their reliability or precision. Whereas, the variance was calculated using the method of ultimate clusters within any domain of estimation.

Detailed information on the sampling design deviation and calculation of the variance is available in the user manual.

Mode of data collection

Face-to-face [f2f]

Research instrument

The PECS questionnaire consists of two main sections:

First section: Certain articles / provisions of the form filled at the beginning of the month,and the remainder filled out at the end of the month. The questionnaire includes the following provisions:

Cover sheet: It contains detailed and particulars of the family, date of visit, particular of the field/office work team, number/sex of the family members.

Statement of the family members: Contains social, economic and demographic particulars of the selected family.

Statement of the long-lasting commodities and income generation activities: Includes a number of basic and indispensable items (i.e, Livestock, or agricultural lands).

Housing Characteristics: Includes information and data pertaining to the housing conditions, including type of shelter, number of rooms, ownership, rent, water, electricity supply, connection to the sewer system, source of cooking and heating fuel, and remoteness/proximity of the house to education and health facilities.

Monthly and Annual Income: Data pertaining to the income of the family is collected from different sources at the end of the registration / recording period.

Second section: The second section of the questionnaire includes a list of 54 consumption and expenditure groups itemized and serially numbered according to its importance to the family. Each of these groups contains important commodities. The number of commodities items in each for all groups stood at 707 commodities and services items. Groups 1-21 include food, drink, and cigarettes. Group 22 includes homemade commodities. Groups 23-45 include all items except for food, drink and cigarettes. Groups 50-54 include all of the long-lasting commodities. Data on each of these groups was collected over different intervals of time so as to reflect expenditure over a period of one full year.

Cleaning operations

Raw Data

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Office.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/compute/recode/rename/format/label harmonized variables.
• A post-harmonization cleaning process is run on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

(3591) households were selected, representing the West Bank and Gaza Strip, (2502) households in the West Bank and (1089) households in Gaza Strip. Excluding the uninhabited housing units, the sample of the survey become (3477) households, (2423) households in the West Bank, and (1054) households in Gaza Strip. A total of (3270) households completed the questionnaire: (2279) household in the West Bank and (991) households in Gaza Strip. The non response rate is, accordingly, 6.3% for all Palestinian territory.

Sampling error estimates

Generally, surveys samples are exposed to two types of errors. The statistical errors, being the first type, result from studying a part of a certain society and not including all its sections. And since the Household Expenditure and Consumption Surveys are conducted using a sample method, statistical errors are then unavoidable. Therefore, a potential sample using a suitable design has been employed whereby each unit of the society has a high chance of selection. Upon calculating the rate of bias in this survey, it appeared that the data is of high quality. The second type of errors is the non-statistical errors that relate to the design of the survey, mechanisms of data collection, and management and analysis of data. Members of the work commission were trained on all possible mechanisms to tackle such potential problems, as well as on how to address cases in which there were no responses (representing 3.4%).

Abstract

The Chókwè Health And Demographic Surveillance System (Chókwè HDSS), is a core research platform of Chókwè Health and Research Centre, affiliated to National Institute of Health, Ministry of Health, Mozambique. The centre is located in Chókwè District, Gaza Province, southern Mozambique., about 230 Km north of the capital Maputo, on the flood plain of the Limpopo River. It was established in June 2010, to provide a platform for implementation and evaluation of clinical trials and health intervention, especially against HIV and related diseases, based on locally generated data.

Chokwe HDSS is a member of the International Network for Demographic Evaluation of the Population and Their Health (INDEPTH), since October 2014. The surveillance area covers an area of approximately 600 square kms within a 25 kms radius of Chokwe City, including 15 (fifteen) villages of which, eight (8) villages are part of Chókwè Municipality (classified as urban) and seven (7) are rural villages namely, Lionde Administrative Post (Lionde Sede, Massavasse, Conhane) and Macarretane (Muzumuia, Matuba, Manjangue and Barragem). The population under surveillance is 97,939 inhabitants (~ 50% of total the district population), in 21,498 households.

The baseline census took place between May and July 2010 and covered all the population of Chókwè City. The census registered 56,727 inhabitants in 12,326 households and each household and individual assigned a unique permanent identification number which enables the follow up of the population. All households are geolocated and enumerated. A resident is defined as any person living in the study area or planning to stay for at least the 3 following months.

Based on recommended INDEPTH methodology for demographic surveillance, monitoring of households and members within households is undertaken in regular 6-month cycles known as 'rounds'. Since its implementation, data collection consists on demographic history including details on birth outcomes (births, still births and abortions), deaths, migration (in-migration and out-migration). The updating of demographic data is done in the three following ways: - Update rounds: In each round, a team of field interviewers and supervisors visit their assigned households to update the demographic data. - Continuous update through community informants: Local leaders report occurring demographic events in their community to the concerned HDSS team.
- Birth and death registrations in health facilities: data collectors are responsible for the daily registration of all births and deaths occurring in the health facilities in the surveillance area.

The data are double entered into a relational database designated Household Registration System (HRS1) implemented in Microsoft Visual FoxPro version 5. Consistence checking and validation are performed and resolved. Verbal autopsy using modified WHO standardized questionnaires, based on physician coded approach has been conducted on all deaths since 2012. Currently, data collection is in the process of migration to electronic data capture and interpretation with InterVA applying the WHO 2012 modified questionnaire.

The Site Leader is Dr Ricardo Thompson.

Geographic coverage

The surveillance area covers an area of approximately 600 square km around Chokwe City (-24.528981, 32.981228), including 15 (fifteen) villages of which, eight (8) villages are part of Chókwè Municipality (classified as urban) and seven (7) are rural villages namely, Lionde Administrative Post (Lionde Sede, Massavasse, Conhane) and Macarretane (Muzumuia, Matuba, Manjangue and Barragem). The population under surveillance is 97,939 inhabitants (~ 50% of total the district population), in 21,498 households.

Analysis unit

Individual

Universe

The population under surveillance is 97,939 inhabitants (~ 50% of total District population), residing in 21498 households. All households and members are assigned a unique identification number (Perm_ID). A member is defined as somebody living in the Demographic Surveillance Area (DSA) for more than three (3) months or intending to remain in the DSA for at least three months.

Kind of data

Event history data

Frequency of data collection

Round (baseline) 1 to Round 2 : once a year Round 3 to 4: twice a year Round 5 : once a year

Sampling procedure

This dataset covers the whole population int he surveillance area.

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

The core HDSS questionnaires are:
1. Household Enumeration and Member Registration Form 2. New Household Form
3. Emigration Registration Form 4. Immigration Registration Form 5. Death Registration Form 6. Pregnancy Registration Form 7. Pregnancy Outcome Registration Form

Response rate

On an average the response rate is 100% over the years for all rounds.

Sampling error estimates

Not Applicable

Data appraisal

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate MZ021 MicroDataCleaned Starts 1 137121 137122 0, 2017-05-23 09:56
MZ021 MicroDataCleaned Transitions 0 318278 318278 0, 2017-05-23 09:56
MZ021 MicroDataCleaned Ends 137122 2017-05-23 09:56
MZ021 MicroDataCleaned SexValues 318278 2017-05-23 09:56
MZ021 MicroDataCleaned DoBValues 318278 2017-05-23 09:56