Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Jan 11;20(1):4.
doi: 10.1186/s12963-022-00283-6.

A method for small-area estimation of population mortality in settings affected by crises

Francesco Checchi  1 , Adrienne Testa  2 , Amy Gimma  2 , Emilie Koum-Besson  2 , Abdihamid Warsame  2
Affiliations

A method for small-area estimation of population mortality in settings affected by crises

Francesco Checchi et al. Popul Health Metr. .

Abstract

Background: Populations affected by crises (armed conflict, food insecurity, natural disasters) are poorly covered by demographic surveillance. As such, crisis-wide estimation of population mortality is extremely challenging, resulting in a lack of evidence to inform humanitarian response and conflict resolution.

Methods: We describe here a 'small-area estimation' method to circumvent these data gaps and quantify both total and excess (i.e. crisis-attributable) death rates and tolls, both overall and for granular geographic (e.g. district) and time (e.g. month) strata. The method is based on analysis of data previously collected by national and humanitarian actors, including ground survey observations of mortality, displacement-adjusted population denominators and datasets of variables that may predict the death rate. We describe the six sequential steps required for the method's implementation and illustrate its recent application in Somalia, South Sudan and northeast Nigeria, based on a generic set of analysis scripts.

Results: Descriptive analysis of ground survey data reveals informative patterns, e.g. concerning the contribution of injuries to overall mortality, or household net migration. Despite some data sparsity, for each crisis that we have applied the method to thus far, available predictor data allow the specification of reasonably predictive mixed effects models of crude and under 5 years death rate, validated using cross-validation. Assumptions about values of the predictors in the absence of a crisis provide counterfactual and excess mortality estimates.

Conclusions: The method enables retrospective estimation of crisis-attributable mortality with considerable geographic and period stratification, and can therefore contribute to better understanding and historical memorialisation of the public health effects of crises. We discuss key limitations and areas for further development.

Keywords: Crisis; Death rate; Displaced; Emergency; Humanitarian; Method; Mortality; Predictive model; Secondary data; Small area estimation; War.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Illustration of actual and counterfactual mortality during and after a hypothetical crisis
Fig. 2
Fig. 2
Coverage of SMART mortality surveys, by state and month, South Sudan, 2013–2018. Heat colours denote the percentage of the state’s population that fell within the sampling frame of at least one survey
Fig. 3
Fig. 3
Trends in selected survey-estimated indicators, South Sudan, 2013–2018. Each dot-line segment denotes the recall period of one survey. Panel A death rate due to injury trauma per 10,000 person-days. Panel B net household migration rate per 1000 person-years
Fig. 4
Fig. 4
Predicted versus observed numbers of deaths per stratum (county), South Sudan, 2013–2018, based on ten-fold cross-validation. The red line indicates perfect fit
See this image and copyright information in PMC

References

    1. Checchi F. Estimation of population mortality in crisis-affected populations: guidance for humanitarian coordination mechanisms. Geneva: World Health Organization; 2018. https://www.who.int/health-cluster/resources/publications/LSHTM-Mortalit....
    1. Heudtlass P, Speybroeck N, Guha-Sapir D. Excess mortality in refugees, internally displaced persons and resident populations in complex humanitarian emergencies (1998–2012)—insights from operational data. Confl Health. 2016;10:15. doi: 10.1186/s13031-016-0082-9. - DOI - PMC - PubMed
    1. Checchi F, Roberts L. Documenting mortality in crises: what keeps us from doing better. PLoS Med. 2008;5:e146. doi: 10.1371/journal.pmed.0050146. - DOI - PMC - PubMed
    1. Checchi F, Warsame A, Treacy-Wong V, Polonsky J, van Ommeren M, Prudhon C. Public health information in crisis-affected populations: a review of methods and their use for advocacy and action. Lancet. 2017;390:2297–2313. doi: 10.1016/S0140-6736(17)30702-X. - DOI - PubMed
    1. Ball P, Betts W, Scheuren F, Dudukovich J, Asher J. Killings and refugee flow in Kosovo, March–June 1999: A report to the International Criminal Tribunal for the Former Yugoslavia. Washington, DC: American Association for the Advancement of Science; 2002. http://www.icty.org/x/file/About/OTP/War_Demographics/en/s_milosevic_kos.... Accessed 6 April 2021.

Publication types