Birth Death Research Articles

Forecasting The Population of China From 2020 To 2025 Based on Random Forest and Linear Regression

The population dynamics of a country do play a vital role in its economic and political development. The COVID-19 epidemic has significantly affected the world's population. However, most people only care about the negative influence caused by COVID-19 but ignore the positive influence. This article uses two machine learning models, the random forest model, and the linear regression model, to predict the population change in China if there were no COVID-19 pandemic. With the predicted results, this article can compare the potential positive impact of the pandemic. This paper tries to fit two popular models, namely, Random Roest and Linear Regression to forecast the population of China from 2020 to 2025. The historical birth rate, death rate, and GDP growth rate of China are collected as features adding to the models to decline the error. For the Random Forest model, this paper set up an ensemble of decision trees to predict the future population of China. For the Linear Regression model, our features and population fit a linear connection. The findings of two models are compared in this article, and it is suggested that the random forest model is more suited for population forecasting. In addition, according to this study, the COVID-19 pandemic has some favorable effects on economic growth and birth rates. The article emphasizes the need to not only focus on the negative effects of the pandemic. Furthermore, the article points out that the linear regression model has poor fitting results for non-linear relationships. It suggests exploring more non-linear models for prediction and considering more influential parameters.

Improved estimation of the relationship between fetal growth and late stillbirth in the United States, 2014–15

In the United States the rate of stillbirth after 28 weeks’ gestation (late stillbirth) is 2.7/1000 births. Fetuses that are small for gestational age (SGA) or large for gestational age (LGA) are at increased risk of stillbirth. SGA and LGA are often categorized as growth or birthweight ≤ 10th and ≥ 90th centile, respectively; however, these cut-offs are arbitrary. We sought to characterize the relationship between birthweight and stillbirth risk in greater detail. Data on singleton births between 28- and 44-weeks’ gestation from 2014 to 2015 were extracted from the US Centers for Disease Control and Prevention live birth and fetal death files. Growth was assessed using customized birthweight centiles (Gestation Related Optimal Weight; GROW). The analyses included logistic regression using SGA/LGA categories and a generalized additive model (GAM) using birthweight centile as a continuous exposure. Although the SGA and LGA categories identified infants at risk of stillbirth, categorical models provided poor fits to the data within the high-risk bins, and in particular markedly underestimated the risk for the extreme centiles. For example, for fetuses in the lowest GROW centile, the observed rate was 39.8/1000 births compared with a predicted rate of 11.7/1000 from the category-based analysis. In contrast, the model-predicted risk from the GAM tracked closely with the observed risk, with the GAM providing an accurate characterization of stillbirth risk across the entire birthweight continuum. This study provides stillbirth risk estimates for each GROW centile, which clinicians can use in conjunction with other clinical details to guide obstetric management.

Trends in racial/ethnic disparities in postpartum hospital readmissions in California from 1997 to 2018

Postpartum readmission is an important indicator of postpartum morbidity. The likelihood of postpartum readmission is highest for Black individuals. However, it is unclear whether the likelihood of postpartum readmission has changed over time according to race/ethnicity. Little is also known about the factors that contribute to these trends. This study aimed to: (1) examine trends in postpartum readmission by race/ethnicity, (2) examine if prenatal or clinical factors explain the trends, and (3) investigate if racial/ethnic disparities changed over time. We examined trends in postpartum readmission, defined as hospitalization within 42 days after birth hospitalization discharge, using live birth and fetal death certificates linked to delivery discharge records from 10,711,289 births in California from 1997 to 2018. We used multivariable logistic regression models that included year and year-squared (to allow for nonlinear trends), overall and stratified by race/ethnicity, to estimate the annual change in postpartum readmission during the study period, represented by odds ratios and 95% confidence intervals. We then adjusted models for prenatal (eg, patient demographics) and clinical (eg, gestational age, mode of birth) factors. To determine whether racial/ethnic disparities changed over time, we calculated risk ratios for 1997 and 2018 by comparing the predicted probabilities from the race-specific, unadjusted logistic regression models. The overall incidence of postpartum readmission was 10 per 1000 births (17.4/1000 births for non-Hispanic Black, 10/1000 for non-Hispanic White, 7.9/1000 for non-Hispanic Asian/Pacific Islander, and 9.6/1000 for Hispanic individuals). Odds of readmission increased for all groups during the study period; the increase was greatest for Black individuals (42% vs 21%-29% for the other groups). After adjustment for prenatal and clinical factors, the increase in odds was similar for Black and White individuals (12%). The disparity in postpartum readmission rates relative to White individuals increased for Black individuals (risk ratio, 1.68 in 1997 and 1.90 in 2018) and more modestly for Hispanic individuals (risk ratio, 1.02 in 1997 and 1.05 in 2018) during the study period. Asian/Pacific Islander individuals continued to have lower risk than White individuals during the study period (risk ratio, 0.87 in 1997 and 0.82 in 2018). The rate of postpartum readmissions increased from 1997 to 2018 in California across all racial/ethnic groups, with the greatest increase observed for Black individuals. Racial/ethnic differences in the trend were more modest after adjustment for prenatal and clinical factors. It is important to find ways to prevent further increases in postpartum readmission, especially among groups at highest risk.

Treats: A modular R package for simulating trees and traits

Abstract Simulating biological realistic data is an important step to understand and investigate biodiversity. Simulated data can be used to generate null, base line or neutral models. These can be used either in comparison to observed data to estimate the mechanisms that generated the data. Or they can be used to explore, understand and develop theoretical advances by proposing toy models. In evolutionary biology, simulations often involve the need of an evolutionary process where descent with modification is at the core of how the simulated data are generated. These evolutionary processes can then be nearly infinitely modified to include complex processes that affect the simulations such as traits co‐evolution, competition mechanisms or mass extinction events. Here I present the treats package, a modular R package for trees and traits simulations. This package is based on a simple birth death algorithm from which all steps can easily be modified by users. treats also provides a tidy interface through the treats object, allowing users to easily run reproducible simulations. It also comes with an extend manual regularly updated following users' questions or suggestions.

Incorporating fossils into the joint inference of phylogeny and biogeography of the tree fern order Cyatheales.

Present-day geographic and phylogenetic patterns often reflect the geological and climatic history of the planet. Neontological distribution data are often sufficient to unravel a lineage's biogeographic history, yet ancestral range inferences can be at odds with fossil evidence. Here, I use the fossilized birth-death process and the dispersal-extinction cladogenesis model to jointly infer the dated phylogeny and range evolution of the tree fern order Cyatheales. I use data for 101 fossil and 442 extant tree ferns to reconstruct the biogeographic history of the group over the last 220 million years. Fossil-aware reconstructions evince a prolonged occupancy of Laurasia over the Triassic-Cretaceous by Cyathealean tree ferns, which is evident in the fossil record but hidden from analyses relying on neontological data alone. Nonetheless, fossil-aware reconstructions are affected by uncertainty in fossils' phylogenetic placement, taphonomic biases, and specimen sampling and are sensitive to interpretation of paleodistributions and how these are scored. The present results highlight the need and challenges of incorporating fossils into joint inferences of phylogeny and biogeography to improve the reliability of ancestral geographic range estimation.

Retrospective Analysis of Clinical Characteristics and Outcomes of Pregnant Women with SARS-CoV-2 Infections Admitted to Intensive Care Units in India (Preg-CoV): A Multicenter Study.

The aim was to examine the outcomes of pregnant women admitted to intensive care unit with coronavirus disease-2019 (COVID-19) infection during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in India. The primary outcome of the study was maternal mortality at day 30. The secondary outcomes were the intensive care unit (ICU) and hospital length of stay, fetal mortality and preterm delivery. This was a retrospective multicentric cohort study. Ethical clearance was obtained. All pregnant women of the 15-45-year age admitted to ICUs with SARS-CoV-2 infection during 1st March 2020 to 31st October, 2021 were included. Data were collected from nine centers and for 211 obstetric patients admitted to the ICU with a confirmed diagnosis of COVID-19. They were divided in to two groups as per their SpO2 (saturation of peripheral oxygen) level at admission on room air, that is, normal SpO2 group (SpO2 > 90%) and low SpO2 group (SpO2 < 90%). The mean age was (30.06 ± 4.25) years and the gestational age was 36 ± 8 weeks. The maternal mortality rate was10.53%. The rate of fetal death and preterm delivery was 7.17 and 28.22%, respectively. The average ICU and hospital length of stay (LOS) were 6.35 ± 8.56 and 6.78 ± 6.04 days, respectively. The maternal mortality (6.21 vs 43.48%, p < 0.001), preterm delivery (26.55 vs 52.17%, p = 0.011) and fetal death (5.08 vs 26.09%, p = 0.003) were significantly higher in the low SpO2 group. The overall maternal mortality among critically ill pregnant women affected with COVID-19 infection was 10.53%. The rate of preterm birth and fetal death were 28.22 and 7.17%, respectively. These adverse maternal and fetal outcomes were significantly higher in those admitted with low SpO2 (<90%) at admission compared with those with normal SpO2. Sinha S, Paul G, Shah BA, Karmata T, Paliwal N, Dobariya J, et al. Retrospective Analysis of Clinical Characteristics and Outcomes of Pregnant Women with SARS-CoV-2 Infections Admitted to Intensive Care Units in India (Preg-CoV): A Multicenter Study. Indian J Crit Care Med 2024;28(3):265-272.

An Age-Period-Cohort Analysis of Cardiovascular Disease Mortality in the United States from 1999 to 2018

BackgroundAlthough cardiovascular disease mortality rates in the United States declined from the 1970s to 2010s, they have now plateaued. The independent effects of age, period, and birth year (cohort) on cardiovascular disease mortality have not previously been defined. MethodsWe used data from the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research to examine the effects of age, period, and cohort on cardiovascular disease mortality among individuals aged 20-84 years from 1999 to 2018, prior to the onset of the coronavirus disease 2019 pandemic. Age effects were described as cardiovascular disease-related mortality rates in each 5-year age group adjusted for year of death (period) and year of birth (cohort). Period and cohort effects were quantified as adjusted rate ratios (RRs) comparing cardiovascular disease mortality rates in each period and cohort to the reference periods and reference cohort (ie, 1919 birth cohort), respectively. ResultsBetween 1999 to 2018, there were 10,404,327 cardiovascular disease deaths among US adults. In each individual birth cohort, the age-specific cardiovascular disease mortality rates were stable between ages 20 through 39 years. Age-specific rates were higher for each year older between ages 40 through 84 years adjusting for period effects. The period cardiovascular disease mortality rates were lower in later periods (2004-2008 period RR 0.87, 95% confidence interval [CI] 0.85 to 0.88; 2009-2013 period RR 0.78, 95% CI 0.76 to 0.80) compared with the reference period (1999 to 2003) and plateaued thereafter. The cohort cardiovascular disease mortality rates were progressively lower in more recent birth cohorts (1924 birth cohort RR 0.85, 95% CI 0.83 to 0.87; 1974 birth cohort RR 0.29, 95% CI 0.27 to 0.32) compared with the reference cohort (1919 cohort) and plateaued thereafter. ConclusionAlthough cardiovascular disease mortality rates declined rapidly among those born between 1919 and 1974, improvements plateaued in birth cohorts thereafter even adjusted for period effects.

Analysis of the causes of death of live newborns of mothers living in Belo Horizonte/MG in the period 2015-2019

The investigation carried out by the committee for the prevention of infant and neonatal deaths is extremely important to understand what made it possible for the death to happen, what is happening to the population and the family. Aiming at the reduction of deaths from preventable causes. For this to happen in a standardized way it is important that the training of professionals is done, correct filling of forms, improving the quality of care to pregnant women, before and after birth, encouraging guidance and autonomy. Objective: To characterize the deaths of newborns from mothers living in Belo Horizonte/MG in the period 2015 to 2019. Methodology: This is a descriptive study with original secondary data made freely available by the Ministry of Health, through the DATASUS Information System and TABNET. Results: Of the 1,041 newborn deaths in BH/MG, it was possible to find the main causes with emphasis on: some disorders originating in the perinatal period and congenital malformation deformities and chromosomal anomalies. Conclusion: Live birth deaths in Belo Horizonte are preventable, monitoring through prenatal consultations, the birth plan, monitoring of the pregnant woman and humanized delivery within the service capable of meeting the pregnant woman's needs would reduce deaths. In addition to providing reliable data for sizing the public budget and developing strategies that prioritize specific actions for prevention and health promotion.

Pólya-splitting distributions as stationary solutions of multivariate birth–death processes under extended neutral theory

Multivariate count distributions are crucial for the inference of ecological processes underpinning biodiversity. In particular, neutral theory provides useful null distributions allowing the evaluation of adaptation or natural selection. In this paper, we build a broader family of multivariate distributions: the Polya-splitting distributions. We show that they emerge naturally as stationary distributions of a multivariate birth–death process. This family of distributions is a consistent extension of non-zero sum neutral models based on a master equation approach. It allows considering both total abundance of the community and relative abundances of species. We emphasize that this family is large enough to encompass various dependence structures among species. We also introduce the strong closure under addition property that can be useful to generate nested multi-level dependence structures. Although all Pólya splitting distributions do not share this property, we provide numerous example verifying it. They include the previously known example with independent species, and also new ones with alternative dependence structures. Overall, we advocate that Polya-splitting distribution should become a part of the classic toolbox for the analysis of multivariate count data in ecology, providing alternative approaches to joint species distribution framework. Comparatively, our approach allows to model dependencies between species at the observation level, while the classical JSDM’s model dependencies at the latent process strata.

A Wideband Non-Stationary 3D GBSM for HAP-MIMO Communication Systems at Millimeter-Wave Bands

High-altitude platforms (HAPs) are considered to be the most important equipment for next-generation wireless communication technologies. In this paper, we investigate the channel characteristics under the configurations of massive multiple-input multiple-output (MIMO) space and large bandwidth at millimeter-wave (mmWave) bands, along with the moving essence of the HAP and ground terminals. A non-stationary three-dimensional (3D) geometry-based stochastic model (GBSM) is proposed for a HAP communication system. We use a cylinder-based geometric modeling method to construct the channel and derive the channel impulse response (CIR). Additionally, the birth–death process of the scatterers is enclosed using the Markov process. Large-scale parameters such as free space loss and rainfall attenuation are also taken into consideration. Due to the relative motion between HAP and ground terminals, the massive MIMO space, and the wide bandwidth in the mmWave band, the channel characteristics of HAP exhibit non-stationarities in time, space, and frequency domains. By deriving the temporal auto-correlation function (ACF), we explore the non-stationarity in the time domain and the impact of various parameters on the correlations across the HAP-MIMO channels. The spatial cross-correlation function (CCF) for massive MIMO scenarios, and the frequency correlation function (FCF) in the mmWave bands are also considered. Moreover, we conduct simulation research using MATLAB. Simulation results show that the theoretical results align well with the simulation results, and this highlights the fact that the constructed 3D GBSM can characterize the non-stationary characteristics of HAP-MIMO channels across the time, space, and frequency domains.

A Non-Stationary Channel Model for 6G Multi-UAV Cooperative Communication

This paper proposes a novel three-dimensional (3D) non-stationary multiple-unmanned aerial vehicle (multi-UAV) cooperative channel model for sixth generation (6G) wireless communication systems. In the proposed multi-UAV cooperative channel model, the channel impulse response (CIR) of sub-channel between each UAV and ground station (GS) is calculated, including line-of-sight (LoS), non-LoS (NLoS), as well as ground reflection transmissions. The relative distance and transmission relationship among sub-channels between multi-UAVs and GS are further modeled and analyzed. To simultaneously capture the cooperative non-stationarity of multi-UAV cooperative channels in space and time domains, a novel cooperation-based space-time (S-T) non-stationary algorithm is developed based on the birth-death (BD) process for the first time. Meanwhile, the UAV-related parameters, e.g., the height and 3D movement of UAVs, are considered. Some important channel statistical properties, such as space-time-frequency correlation function (STF-CF), Doppler power spectral density (DPSD), cooperative time stationary interval, and singular value spread (SVS), are obtained. Based on the simulation results, multi-UAV cooperative channel statistical properties are analyzed. Finally, the simulation results match well with the ray-tracing results, which validates the accuracy of the proposed multi-UAV channel model.

Short Term Coping-Behaviors and Postpartum Health in a Population-Based Study of Women with a Live Birth, Stillbirth, or Neonatal Death.

Responding to the National Institutes of Health Working Group's call for research on the psychological impact of stillbirth, we compared coping-related behaviors by outcome of an index birth (surviving live birth or perinatal loss - stillbirth or neonatal death) and, among individuals with loss, characterized coping strategies and their association with depressive symptoms 6-36 months postpartum. We used data from the Stillbirth Collaborative Research Network follow-up study (2006-2008) of 285 individuals who experienced a stillbirth, 691 a livebirth, and 49 a neonatal death. We conducted a thematic analysis of coping strategies individuals recommended following their loss. We fit logistic regression models, accounting for sampling and inverse probability of follow-up weights to estimate associations between pregnancy outcomes and coping-related behaviors and, separately, coping strategies and probable depression (Edinburgh Postnatal Depression Scale > 12) for those with loss. Compared to those with a surviving live birth and adjusting for pre-pregnancy drinking and smoking, history of stillbirth, and age, individuals who experienced a loss were more likely to report increased drinking or smoking in the two months postpartum (adjusted OR: 2.7, 95% CI = 1.4-5.4). Those who smoked or drank more had greater odds of probable depression at 6 to 36 months postpartum (adjusted OR 6.4, 95% CI = 2.5-16.4). Among those with loss, recommended coping strategies commonly included communication, support groups, memorializing the loss, and spirituality. Access to a variety of evidence-based and culturally-appropriate positive coping strategies may help individuals experiencing perinatal loss avoid adverse health consequences.

Moment Closure for a Birth-Death Model of Antimicrobial Heteroresistance

Developing predictive Antimicrobial Resistance (AMR) models supporting optimal treatment design to combat ”superbugs” poses a significant challenge for mathematical biology. Birth-Death (BD) processes constitute an intuitive and flexible approach for modelling biological systems’ stochastic dynamics that is regaining attention due to the advances in computational techniques. This work presents a multivariate BD model of antimicrobial heteroresistance, a phenotype in which a bacterial isolate contains many subpopulations with heterogeneous antimicrobial responses. The model includes Lotka-Volterra competition between subpopulations, leading to an infinite coupled system of equations for the moment dynamics of the BD process. Then, a moment closure is proposed by assuming a log-normal distribution for a univariate BD process approximating the total population behaviour. The results are compared with stochastic simulations of the multivariate BD process during a typical time-kill assay.

АНАЛІЗ ВІТЧИЗНЯНОГО РИНКУ ПРАЦІ В УМОВАХ ВІЙНИ

The article examines the economic and demographic factors characterizing the population. The population is the main carrier of the labor resource and entrepreneurial spirit. Thanks to its knowledge, skills and abilities, the economic resource of labor acquires special importance in the modern conditions of the knowledge economy. It becomes the most important of all factors of economic growth and development. An economically active population directly affects the functioning of the labor market in the economic system. The economic activity of the population depends on the processes of reproduction and migration. The level of employment, age and social structure of labor resources affects the country’s labor supply. All this determines the relevance of the research topic and requires a detailed analysis of problems related to the peculiarities of the functioning of the domestic labor market in the modern market economy. During the war in Ukraine, the labor market is faced with many problems that require urgent study and solution: population decline, birth rate reduction and death rate increase, aging of the nation, increase in unemployment rate, intensification of migration flows, etc. This situation is aggravated due to the reduction of production, the closure of many firms due to military operations. External forced migration has intensified in Ukraine, which causes significant psychological problems: anxiety, depression, fear, despair. It differs from labor migration in terms of duration and structure. Reconstruction and restoration of Ukraine after the war will require, first of all, human capital with its physical and mental abilities, powerful intellectual potential. It is extremely important to return migrants to their homeland, to include them in the economically active population of our country and to create a gross domestic product. In addition to migration policy, labor market regulation by the state should include appropriate demographic policy, employment policy, as well as social and personnel policy. The active policy of the state in the labor market involves the development of a mechanism for institutional, informational and legal support for the implementation of a unified strategy for human resources management.

Nicolaus Copernicus and medicine - 550th anniversary of the birth and 480th anniversary of the death of a scientist who turned the view of the world upside down

This year sees the 550th anniversary of the birth and 480th anniversary of the death of Nicolaus Copernicus, internationally recognized as the father of modern astronomy, who ?stopped the Sun, moved the Earth? and turned the view of the world upside down. However, the fame of Nicolaus Copernicus is not referred only to the fields of astronomy, mathematics, canon and civil law, as well as theology, economy and diplomacy. This Renaissance polymath was also one of the most respected practicing physicians at the time. Noteworthy, Nicolaus Copernicus paid special attention to the poor, supplying them with free medical advice, assistance and medicines. Therefore, our paper deals with this less known aspect of the famous scientist?s life.

ДЕМОГРАФИЧЕСКАЯ СИТУАЦИЯ В РЕСПУБЛИКАХ СЕВЕРО-КАВКАЗСКОГО ФЕДЕРАЛЬНОГО ОКРУГА: НАСТОЯЩЕЕ И БУДУЩЕЕ

In this article we will analyze the demographic situation in the Russian Federation and in North Ossetia-Alania, in particular. The study revealed the existing problems in this area, as well as the causes of the law birth and high death rate. During the research we used data from official websites such Government of the Russian Federation, the Government of the Republic of North Ossetia-Alania, Rosstat and other available publications on the topic of the study were studied. The information obtained made it possible to analyze the relationship between the socio-economic level of the country and the subject and the state of the demographic situation. On the basis of theoretical materials and practical results of the survey, the possible development of demographic processes is predicted, taking into account the measures taken by the authorities to support the population.

Spatial Distribution of Population in Nepal: On the Basis of 2078 Census

The indicators of population change, which would affect distribution, include birth rate, death rate, immigration, and emigration. Significant adjustments to any of these indicators can alter how a population is distributed. The general patterns to the distribution of a population are known as spatial distribution patterns. Spatial distribution patterns can be uniform, random, or clumped. Additionally, population distribution is affected by population density, which is the number of individuals within a given area. This paper based on the major aspects of population changes i.e. size, growth and distribution of population in Nepal and based on censuses data over time. Population size and growth rate has been increasing over the time. It has rapidly increased since 1961—2011. In 2021 census, total population are 29.1 million, which is an increase of 10.1 million when compared to 26.4 million population recorded in 2011 census with an average annual growth rate of 0.93 percent (2021) lower than 1.35 percent growth rate reported in 2011 census. Tarai accounts 53.6 percent of the total population with percentage of average annual growth rate 1.56. By province level, Madhesh province holds more than twenty percent of the population of the country (i.e. 20.99 %) and an average annual growth rate 1.20 percent. It may be due to the inclusion Tarai in this region. The highest population growth rate is found in Bhaktapur district (3.32 %) and while the least is in Ramechhap (- 1.65 %). Overall the current dramatic decline in the population growth rate may be attributed to the absence heavy cause behind migration in various reasons.

Adverse Maternal and Fetal Outcomes in Teenage Pregnancy

INTRODUCTION: Teenage pregnancy is a major public health issue these days and is associated with adverse maternal and fetal outcomes. This study was conducted to determine the adverse maternal and fetal outcomes in teenage pregnancy. MATERIALS AND METHODS: This was a hospital based descriptive cross-sectional study. All the teenage pregnant women (15-19 years of age) with a singleton pregnancy coming to antenatal ward of Birat Medical College Teaching Hospital from 22nd December 2022 to 21th December 2023 were enrolled in the study, irrespective of their APGAR score at birth, NICU admission and early neonatal death and intrauterine fetal death were noted after delivery. RESULTS: The incidence of teenage pregnancy was 1.7%, and the mean age was 18.36±.83 years. Majority (53.3 %) of the women had normal vaginal delivery. The most common maternal complication was preterm labor (26.7%), while the most common fetal complication was low birth weight (38.7%). 29.3% were admitted to NICU, 25.3% had low APGAR score, 2.7% had stillbirth, 1.3% had early neonatal death. CONCLUSION: Teenage pregnancy was associated with a high rate of adverse maternal and fetal outcomes like premature delivery, anemia, pregnancy induced hypertension, instrumental deliveries, lower segment cesarean section (LSCS), low birth weight, low APGAR score at birth and NICU admission.

Analisi Dampak Bisnis Internasional Terhadap Pertumbuhan Perekonomian Di Indonesia

International Trade is an economic transaction carried out between countries. Among the items commonly stored are consumer goods, such as televisions and clothing; capital goods, such as machinery, raw materials and food. In almost all countries, international trade is an effort to increase GDP. Economic growth is an increase in the ability of a country's economy to produce both goods and services in quantity. In general, the high or low population of a country, the birth rate and death rate greatly influence a country's economy because productivity, education, and investment in physical capital since improving longevity create greater needs. The type of research used is qualitative research, qualitative research is research that produces several findings that cannot be obtained using statistical procedures or quantitative methods. With the existence of International Business in Indonesia, Economic Growth will increase. The reason is that the supply and increase for foreign products from the Indonesian people will continue to increase. For this reason, companies or industries in Indonesia will often experience increases and growth, such as the development of the textile, shrimp, coffee and so on industries. With the existence of international business, the prosperity and welfare of society in Indonesia is developing well due to the opening of various kinds of employment opportunities, so that there can be a reduction in the level of poverty in Indonesia.

Non-linear model of the macroeconomic system dynamics: multiplier-accelerator

The article discusses one of the classic problems of macroeconomic dynamics, on which the neo-Keynesian theory of growth is based, so that the interaction between the multiplier and the accelerator. A new approach was proposed to develop a mathematical model of the dynamics of the mutual multiplier, which indicates the marginal propensity to save as a result of the GDP growth, and the accelerator, which reflects the growth of capital of the national income in the multiplier. The model is based on the hypothesis of non-linear dependence of the consumption on the amount of profit. This assumes that consumption growth is limited, i.e., a saturation effect occurs. In addition, the model took into account the delayed reaction of the accelerator to the influence of the multiplier. Under building the model, the considered processes were considered continuous in time. This made it possible to provide the mathematical model ”accelerator - multiplier” as a system of two differential equations of the first order. The application of the developed model to the analysis of the dynamic properties of the macroeconomic system makes it possible to evaluate the parameters at which the ”multiplier-accelerator” system enters a critical state. It has been proven that the conditions for the occurrence of self-oscillations depend on the critical value of the accelerator power. The presence of a two-fold limit cycle with corresponding ”soft” and ”hard” modes of birth (death) of the limit cycle was also founded. The applied usefulness of the model is that the choice of management decisions taking into account these results allow us preventing the occurrence of bifurcations and disasters in the process of evolution of the macroeconomic systems.