Characteristics and health outcomes of internally displaced population in unofficial rural self-settled camps after the 2005 Kashmir, Pakistan earthquake

2010 ◽  
Vol 17 (3) ◽  
pp. 136-141 ◽  
Author(s):  
Emily Y.Y. Chan ◽  
Jacqueline J. Kim
2004 ◽  
Vol 8 (38) ◽  
Author(s):  
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...  

Summary of new report published by WHO, assessing the current health status of the internally displaced people in Darfur, Sudan,


2014 ◽  
Vol 5 (3) ◽  
pp. 18-21 ◽  
Author(s):  
Edwin Benny ◽  
Kelly Mesere ◽  
Boris I Pavlin ◽  
Logan Yakam ◽  
Rebecca Ford ◽  
...  

2019 ◽  
Vol 14 (3) ◽  
pp. 302-307
Author(s):  
Benjamin Q. Huynh ◽  
Sanjay Basu

ABSTRACTObjectives:Armed conflict has contributed to an unprecedented number of internally displaced persons (IDPs), individuals who are forced out of their homes but remain within their country. IDPs often urgently require shelter, food, and healthcare, yet prediction of when IDPs will migrate to an area remains a major challenge for aid delivery organizations. We sought to develop an IDP migration forecasting framework that could empower humanitarian aid groups to more effectively allocate resources during conflicts.Methods:We modeled monthly IDP migration between provinces within Syria and within Yemen using data on food prices, fuel prices, wages, location, time, and conflict reports. We compared machine learning methods with baseline persistence methods of forecasting.Results:We found a machine learning approach that more accurately forecast migration trends than baseline persistence methods. A random forest model outperformed the best persistence model in terms of root mean square error of log migration by 26% and 17% for the Syria and Yemen datasets, respectively.Conclusions:Integrating diverse data sources into a machine learning model appears to improve IDP migration prediction. Further work should examine whether implementation of such models can enable proactive aid allocation for IDPs in anticipation of forecast arrivals.


2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Isabel Garcés-palacio ◽  
Mary Salazar-Barrientos ◽  
Edison Bedoya Bedoya ◽  
Ana Langer

Abstract Background Colombia has been affected by internal armed conflict for 70 years. About 7.3 million people have been internally displaced and nearly 50% of them were women. In conflict-afflicted areas, pregnant women and newborns have higher rates of adverse health outcomes. Methods Secondary analysis of public databases. We examined sixteen indicators from the Countdown to 2030 initiative, for which data from Colombia were available and reliable between 1998 and 2016. We also constructed a variable (victimization rate) to measure the intensity of the conflict for each municipality/year and grouped them into quintiles. We compared relative differences and confidence intervals using the Rothman and Greenland method. Results Across time, most indicators improved in all municipalities. However, four indicators were significantly different between municipalities with high versus low victimization rates. The maternal mortality ratio was higher in the municipalities with higher victimization rates in the periods 1998-2004, 2005-2011 and 2012-2016. The percentages of caesarean births and women who received four or more antenatal care visits were lower in settings with highest levels of victimization (1998-2000,) while the fertility rate among women 15-19 years old was higher in those municipalities between 2012 and 2016. Conclusions In Colombia, several maternal and child health indicators have improved during the years of the conflict; however, municipalities most affected by the armed conflict had poorer reproductive and maternal health outcomes. Key messages Maternal and reproductive health were negatively affected by protracted armed conflict in Colombia.


2014 ◽  
Vol 13 (2) ◽  
pp. 362-370 ◽  
Author(s):  
Jeroen H. J. Ensink ◽  
Andy Bastable ◽  
Sandy Cairncross

The performance and acceptability of the NeroxTM membrane drinking water filter were evaluated among an internally displaced population in Pakistan. The membrane filter and a control ceramic candle filter were distributed to over 3,000 households. Following a 6-month period, 230 households were visited and filter performance and use were assessed. Only 6% of the visited households still had a functioning filter, and the removal performance ranged from 80 to 93%. High turbidity in source water (irrigation canals), together with high temperatures and large family size were likely to have contributed to poor performance and uptake of the filters.


2011 ◽  
Vol 26 (S1) ◽  
pp. s59-s59
Author(s):  
E.K. Vithana

BackgroundSri Lanka's 28 year protracted civil conflict between the government forces and Liberation Tigers of Tamil Eelam (LTTE) in the North of country saw dramatic end by May 2009 when the military forces succeeded in crushing the LTTE. Around 300,000 people were displaced due to the conflict and they were settled in welfare villages established in the North.DiscussionThe Government of Sri Lanka working in partnership with all other actors mounted a major humanitarian response to address the needs of the war displaced population. The Ministry of Health took a leading role in coordinating the health care programs for the Internally Displaced Population(IDP).ObservationsHigher morbidity and mortality observed during early phase of settlement of IDPs was due to the results of two scenarios, one being the conflict situation and its direct consequences that have caused injuries, disabilities and mental trauma among the population. The second being the result of the collapse of the health system in conflict affected areas, long period of displacement of people and the disruption of social structures that have led to the indirect consequences of increase of infectious diseases and worsening of chronic diseases. Ministry of Health used Daily Crude Mortality Rate (DCMR) to measure the success of the response. According to the Sphere Project guidelines that developed a set of minimum standards in a disaster situation, the DCMR should be 0.25 per 10 000 population for South East Asia. The emergency threshold level is 0.5 per 10 000 per day for this region.ConclusionsOf the number of people reaching the IDP welfare villages in early stages of emergency phase in May, DCMR averaged to 0.7. The figure settled to less than 0.5 per 10000 in June 2009. Thereafter daily DCMR remained less than 0.5 indicating success of the provision of care for IDPS.


Author(s):  
Winifred Ekezie ◽  
Puja Myles ◽  
Rachael L Murray ◽  
Manpreet Bains ◽  
Stephen Timmons ◽  
...  

ABSTRACT Background Conflict in Nigeria displaced millions of people, and some settled in camp-like locations within the country. Evidence on the association between living conditions and health outcomes among these populations are limited. This study investigated the risk factors associated with illnesses among camp-dwelling internally displaced persons (IDPs) in northern Nigeria. Methods A cross-sectional study was conducted in nine camps in 2016. Self-reported data on socio-demography, resource utilization and disease outcomes were collected. Association between health conditions and various factors, including sanitation and healthcare access, was investigated. Results Data from 2253 IDPs showed 81.1% (CI = 79.5–82.7) experienced one or more health conditions; however, over 20% did not access healthcare services. Most common diseases were malaria, fever, typhoid and diarrhoea. Multivariable logistic regression presented as adjusted odds ratios(aOR) and 95% confidence intervals(CIs) showed factors significantly associated with increased likelihood of illnesses included being female (aOR = 1.53;CI = 1.19–1.96), overcrowding (aOR = 1.07;CI = 1.00–1.36), long-term conditions (aOR = 2.72;CI = 1.88–3.94), outdoor defecation (aOR = 2.37;CI = 1.14–4.94) and presence of disease-causing vectors (aOR = 3.71;CI = 1.60–8.60). Conclusion Most diseases in the camps were communicable. Modifiable risk factors such as overcrowding and poor toilet facilities were associated with increased poor health outcomes. This evidence highlights areas of high priority when planning humanitarian public health interventions.


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