The world's Jewish population has had a complex and tumultuous history over the past millennia, regularly dealing with persecution, pogroms, and even genocide. The legacy of expulsion and persecution of Jews, including bans on land ownership, meant that Jewish communities disproportionately lived in urban areas, working as artisans or traders, and often lived in their own settlements separate to the rest of the urban population. This separation contributed to the impression that events such as pandemics, famines, or economic shocks did not affect Jews as much as other populations, and such factors came to form the basis of the mistrust and stereotypes of wealth (characterized as greed) that have made up anti-Semitic rhetoric for centuries. Development since the Middle Ages The concentration of Jewish populations across the world has shifted across different centuries. In the Middle Ages, the largest Jewish populations were found in Palestine and the wider Levant region, with other sizeable populations in present-day France, Italy, and Spain. Later, however, the Jewish disapora became increasingly concentrated in Eastern Europe after waves of pogroms in the west saw Jewish communities move eastward. Poland in particular was often considered a refuge for Jews from the late-Middle Ages until the 18th century, when it was then partitioned between Austria, Prussia, and Russia, and persecution increased. Push factors such as major pogroms in the Russian Empire in the 19th century and growing oppression in the west during the interwar period then saw many Jews migrate to the United States in search of opportunity.

Jews were the dominant religious group in the Israel-Palestine region at the beginning of the first millennia CE, and are the dominant religious group there today, however, there was a period of almost 2,000 years where most of the world's Jews were displaced from their spiritual homeland. Antiquity to the 20th century Jewish hegemony in the region began changing after a series of revolts against Roman rule led to mass expulsions and emigration. Roman control saw severe persecution of Jewish and Christian populations, but this changed when the Byzantine Empire adopted Christianity as its official religion in the 4th century. Christianity then dominated until the 7th century, when the Rashidun Caliphate (the first to succeed Muhammad) took control of the Levant. Control of region split between Christians and Muslims intermittently between the 11th and 13th centuries during the Crusades, although the population remained overwhelmingly Muslim. Zionism until today Through the Paris Peace Conference, the British took control of Palestine in 1920. The Jewish population began growing through the Zionist Movement after the 1880s, which sought to establish a Jewish state in Palestine. Rising anti-Semitism in Europe accelerated this in the interwar period, and in the aftermath of the Holocaust, many European Jews chose to leave the continent. The United Nations tried facilitating the foundation of separate Jewish and Arab states, yet neither side was willing to concede territory, leading to a civil war and a joint invasion from seven Arab states. Yet the Jews maintained control of their territory and took large parts of the proposed Arab territory, forming the Jewish-majority state of Israel in 1948, and acheiving a ceasefire the following year. Over 750,000 Palestinians were displaced as a result of this conflict, while most Jews from the Arab eventually fled to Israel. Since this time, Israel has become one of the richest and advanced countries in the world, however, Palestine has been under Israeli military occupation since the 1960s and there are large disparities in living standards between the two regions.

Israel IL: Age Dependency Ratio: % of Working-Age Population data was reported at 65.551 % in 2017. This records an increase from the previous number of 64.950 % for 2016. Israel IL: Age Dependency Ratio: % of Working-Age Population data is updated yearly, averaging 65.495 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 71.608 % in 1982 and a record low of 60.294 % in 2008. Israel IL: Age Dependency Ratio: % of Working-Age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Israel – Table IL.World Bank: Population and Urbanization Statistics. Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: this indicator implies the dependency burden that the working-age population bears in relation to children and the elderly. Many times single or widowed women who are the sole caregiver of a household have a high dependency ratio.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Mosaiced 100m resolution global datasets. The methodology used to estimate the annual subnational census-based figures can be found in LLoyd et al (https://www. tandfonline.com/doi/full/10.1080/20964471.2019.1625151). The mapping approach is Random Forest-based dasymetric redistribution. More info at: www.worldpop.org.

As of the end of 2020, the State of Israel, with a population of 9.3 million, had administered more COVID-19 vaccine doses than all countries aside from China, the US, and the UK. Moreover, Israel had administered almost 11.0 doses per 100 population, while the next highest rates were 3.5 (in Bahrain) and 1.4 (in the United Kingdom). All other countries had administered less than 1 dose per 100 population. While Israel’s rollout of COVID-19 vaccinations was not problem-free, its initial phase had clearly been rapid and effective. A large number of factors contributed to this early success, and they can be divided into three major groups. The first group of factors consists of long-standing characteristics of Israel which are extrinsic to health care. They include: Israel’s small size (in terms of both area and population), a relatively young population, relatively warm weather in December 2020, a centralized national system of government, and well-developed infrastructure for implementing prompt responses to large-scale national emergencies. The second group of factors are also long-standing, but they are health-system specific. They include: the organizational, IT and logistical capacities of Israel’s community-based health care providers, the availability of a cadre of well-trained, salaried, community-based nurses who are directly employed by those providers, a tradition of effective cooperation between government, health plans, hospitals, and emergency care providers – particularly during national emergencies; and support tools and decisionmaking frameworks to support vaccination campaigns. The third group consists of factors that are more recent and are specific to the COVID-19 vaccination effort. They include: the mobilization of special government funding for vaccine purchase and distribution, timely contracting for a large amount of vaccines relative to Israel’s population, the use of simple, clear and easily implementable criteria for determining who had priority for receiving vaccines in the early phases of the distribution process, a creative technical response that addressed the demanding cold storage requirements of the Pfizer-BioNTech COVID-19 vaccine, and well-tailored outreach efforts to encourage Israelis to sign up for vaccinations and then show up to get vaccinated. While many of these facilitating factors are not unique to Israel, part of what made the Israeli rollout successful was its combination of facilitating factors (as opposed to each factor being unique separately) and the synergies it created among them. Moreover, some high-income countries (including the US, the UK, and Canada) are lacking several of these facilitating factors, apparently contributing to the slower pace of the rollout in those countries.

A data set designed to provide a cross-sectional description of health, mental, and social status of the oldest-old segment of the elderly population in Israel, and to serve as a baseline for a multiple-stage research program to correlate demographic, health, and functional status with subsequent mortality, selected morbidity, and institutionalization. Study data are based on a sample of Jewish subjects aged 75+, alive and living in Israel on January 1, 1989, randomly selected from the National Population Register (NPR), a complete listing of the Israeli population maintained by the Ministry of the Interior. The NPR is updated on a routine basis with births, deaths, and in and out migration, and corrected by linkage with census data. The sample was stratified by age (five 5-year age groups: 75-79, 80-84, 85-89, 90-94, 95+), sex, and place of birth (Israel, Asia-Africa, Europe-America). One hundred subjects were randomly selected in each of the 30 strata. However, there were less than 100 individuals of each sex aged 95+ born in Israel, so all were selected for the sample. The total group included 2,891 individuals living both in the community and in institutions. A total of 1,820 (76%) of the 75-94 age group were interviewed during 1989-1992. An additional cognitive exam (Folstein) and a 24-hour dietary recall interview were added in the second round. Kibbutz Residents Sample The kibbutz is a social and economic unit based on equality among members, common property and work, collaborative consumption, and democracy in decision making. There are 250 kibbutzim in Israel, and their population constitutes about 3% of the country''s total population. All kibbutz residents in the country aged 85+, both members and parents, were selected for interviewing, of whom 80.4% (n=652) were interviewed. A matched sample aged 75-84 was selected, and 85.9% (n=674) were successfully interviewed. The original interview took approximately two hours to administer, and collected extensive information concerning the socio-demographic, physical, health, functioning, life events (including Holocaust), depression, mental status, and social network characteristics of the sample. The questionnaire used for kibbutz residents in the follow-up interview is identical to that utilized in the national random sample. Data Availability: Mortality data for both the national and kibbutz samples are available for analysis as a result of the linkage to the NPR file updated as of June 2000. The fieldwork for first follow up was completed as of September 1994 and for the second follow up as of December 2002. The data file of the three phases of the study is ready for analysis. * Dates of Study: 1989-1992 * Study Features: Longitudinal, International * Sample Size: 2,891

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

National

Analysis unit

Household Individual

Universe

National population, both sexes,18 and more years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 1199

The sample was not designed to be representative of the entire adult population. We excluded the non-urban population (communities that include less than 2000 people) which constitutes 9% of the Israeli population. There were different stages in the sampling procedure: - Division into strata (based on geographic location, community size and socio-economic characteristics). - With strata sampling of statistical areas (the smallest ecological unit). - Interviewing of specified number of persons within statistical units based on Kish-grid.

Stratification factors were used such as: - Socio-economic characteristics of statistical area - Geographical region of statistical area.

Remarks about sampling: - Final numbers of clusters or sapling points: 47 - Sample unit from office sampling: Address point in the selection area, and the procedures for continued movement.

Mode of data collection

Face-to-face [f2f]

Research instrument

The WVS questionnaire was translated from the English questionnaire by a member of the research team. The questionnaire was translated to Hebrew and Arabic. The translated questionnaire was back-translated into English and the translated questionnaire was also pre-tested with 10 face to face interviews. We used the ISSP questionnaire for the demographic questions. There have been some optional questions included: V120-121, V124-125, V36, V133, V139, V217, V83-85, V97-102. There have been some country-specific questions included in the questionnaire but there have not been included before the demographic questions. The questions included were: b38-b42b45b46, b48-b61,b63-b80 were country-specific. Also, it is important to mention that not all the questions were in the prescribed order. The sample was not designed to be representative of the entire adult population. We excluded the non-urban population (communities that include less than 2000 people) which constitutes 9% of the Israeli population. The lower age cut-off for the sample was 18 and there was not any upper age cut-off for the sample.

Response rate

The following table presents completion rate results: -Total number of starting names/addresses 3617 - Addresses established as empty, demolished or containing no private dwellings 241 - Selected Respondent had inadequate understanding of language of survey 278 -No contact at selected address 296 -No refusal at selected address 1367 -Other type of unproductive (please write in full details in the box below) 236 -Full productive interview 1199

Sampling error estimates

Estimated error: 2.9

IL：人口超过100万的城市群人口在12-01-2017达4,832,239.000人，相较于12-01-2016的4,766,246.000人有所增长。IL：人口超过100万的城市群人口数据按年更新，12-01-1960至12-01-2017期间平均值为2,575,652.000人，共58份观测结果。该数据的历史最高值出现于12-01-2017，达4,832,239.000人，而历史最低值则出现于12-01-1960，为992,763.000人。CEIC提供的IL：人口超过100万的城市群人口数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的以色列 – 表 IL.世界银行：人口和城市化进程统计。