However, tracking countries with the largest net net transition with immigration numbers exceeding the number of immigrants can provide valuable insight into recent political and economic developments.
Net transition loss: the most intense hit country
According to the United Nations World Population Outlook 2024, Pakistan recorded the highest net population loss due to migration in 2023, with around 1.6 million leaving the country than about 1.6 million people arrived. Other Asian countries, including India (-980,000), China (-570,000), and Bangladesh (-550,000), have also experienced significant outflows.
The list includes countries with at least 10,000 immigrants than immigrants. These figures become clear and highlight widespread instability and inequality across different regions.
Rank Country Net Move 1 Pakistan-1.62m 2 Sudan-1.35m 3 India-979K 4 China-568K 5 Bangladesh-550K 6 Nepal-410K 7 Turkey-318K 8 Ukraine-300K 9 Brazil-240K 10 Philippines-164KKK
Conflict-led escape from Sudan
Located in Northeast Africa, Sudan witnessed a net loss of around 1 million in 2023. This is largely due to a catastrophic civil war between the Sudanese Army (SAF) and the Paramilitary Rapid Support Forces (RSF).
The humanitarian crisis forced many to flee the country in search of safety. A spokesman for a doctor without borders described the situation as including “a horrifying level of violence” that was inflicted on civilians.
Economic and migration political factors
The data draws a broader picture of mobility trends. There, it falls into two general categories: those that are experiencing economic difficulties (such as Pakistan, India, China) and those that are suffering from active conflicts (such as Sudan, Ukraine, Palestine).
In many cases, both economic and political pressures are intertwined, strengthening each other and accelerating the resignation of residents.
Examining these transition patterns reveals that international transitions are not merely personal decisions, but rather reflect systemic issues that require global attention.