"Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.This dataset includes demographic data of 22 countries from 1960 to 2018, including Sri Lanka, Bangladesh, Pakistan, India, Maldives, etc. Data fields include: country, year, population ratio, male ratio, female ratio, population density (km). Source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision. ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme. Periodicity: Annual Statistical Concept and Methodology: Population estimates are usually based on national population censuses. Estimates for the years before and after the census are interpolations or extrapolations based on demographic models. Errors and undercounting occur even in high-income countries. In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census. The quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data. The currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census. The United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems. International migration is the only other factor besides birth and death rates that directly determines a country's population growth. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect. Population projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant."

This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Maternal and child mortality rates remain a significant concern in South Asian countries, primarily due to limited access to maternal care services and socioeconomic disparities. While previous studies have examined the factors influencing the utilization of antenatal care (ANC) services in individual countries, there is a lack of comparative analysis across South Asian nations. This study aims to investigate the factors affecting ANC utilization among women aged 15–49 in Bangladesh, India, Nepal, Maldives, and Pakistan using the latest Demographic and Health Survey data. The study utilized a total weighted sample size of 262,531 women. Simple bivariate statistics and binary logistic regression were employed to identify potential factors influencing ANC utilization. Decomposition analysis and concentration curve (Lorenz curve) were used to assess inequality in ANC service utilization. The prevalence of ANC utilization varied across the countries, with Maldives having the highest (96.83%) and Bangladesh the lowest (47.01%). Women’s and husbands’ education, household wealth status, BMI, and urban residence were found to significantly influence maternal healthcare services utilization. Higher education levels, affluent wealth quintiles, and urban living were identified as significant contributors to socioeconomic disparities in accessing ANC services. This study highlights the crucial role of socioeconomic factors in the utilization of maternal healthcare services in South Asian countries. Governments should focus on improving healthcare infrastructure, addressing cultural barriers, and promoting education to address these disparities. Identifying context-specific causes of maternal healthcare utilization is essential to inform targeted interventions and policies aimed at improving access to ANC services and reducing maternal mortality rates.

BackgroundMulti-drug resistant typhoid fever remains an enormous public health threat in low and middle-income countries. However, we still lack a detailed understanding of the epidemiology and genomics of S. Typhi in many regions. Here we have undertaken a detailed genomic analysis of typhoid in urban Dhaka, Bangladesh to unravel the population structure and antimicrobial resistance patterns in S. Typhi isolated between 2004–2016.Principal findingsWhole genome sequencing of 202 S. Typhi isolates obtained from three study locations in urban Dhaka revealed a diverse range of S. Typhi genotypes and AMR profiles. The bacterial population within Dhaka were relatively homogenous with little stratification between different healthcare facilities or age groups. We also observed evidence of exchange of Bangladeshi genotypes with neighboring South Asian countries (India, Pakistan and Nepal) suggesting these are circulating throughout the region. This analysis revealed a decline in H58 (genotype 4.3.1) isolates from 2011 onwards, coinciding with a rise in a diverse range of non-H58 genotypes and a simultaneous rise in isolates with reduced susceptibility to fluoroquinolones, potentially reflecting a change in treatment practices. We identified a novel S. Typhi genotype, subclade 3.3.2 (previously defined only to clade level, 3.3), which formed two localized clusters (3.3.2.Bd1 and 3.3.2.Bd2) associated with different mutations in the Quinolone Resistance Determining Region (QRDR) of gene gyrA.SignificanceOur analysis of S. Typhi isolates from urban Dhaka, Bangladesh isolated over a twelve year period identified a diverse range of AMR profiles and genotypes. The observed increase in non-H58 genotypes associated with reduced fluoroquinolone susceptibility may reflect a change in treatment practice in this region and highlights the importance of continued molecular surveillance to monitor the ongoing evolution of AMR in Dhaka. We have defined new genotypes and lineages of Bangladeshi S. Typhi which will facilitate the identification of these emerging AMR clones in future surveillance efforts.