The Impact of Armed Conflict on the Epidemiological Situation of COVID-19 in Libya, Syria and Yemen

Abstract

Background: Since the Arab uprising in 2011, Libya, Syria and Yemen have gone through major internal armed conflicts. This resulted in large numbers of deaths, injuries, and population displacements, with collapse of the healthcare systems. Furthermore, the situation was complicated by the emergence of COVID-19 as a global pandemic, which made the populations of these countries struggle under unusual conditions to deal with both the pandemic and the ongoing wars. This study aimed to determine the impact of the armed conflicts on the epidemiology of the novel coronavirus (SARS-CoV-2) within these war-torn countries and highlight the strategies needed to combat the spread of the pandemic and its consequences.Methods: Official and public data concerning the dynamics of the armed conflicts and the spread of SARS-COV-2 in Libya, Syria and Yemen were collected from all available sources, starting from the emergence of COVID-19 in each country until the end of December 2020. Datasets were analyzed by a set of statistical techniques and the weekly resolved data were used to probe the link between the intensity levels of the conflict and the prevalence of COVID-19.Results: The data indicated that there was an increase in the intensity of the violence at an early stage from March to August 2020, when it approximately doubled in the three countries, particularly in Libya. During that period, few cases of COVID-19 were reported, ranging from 5 to 53 cases/day. From September to December 2020, a significant decline in the intensity of the armed conflicts was accompanied by steep upsurges in the rate of COVID-19 cases, which reached up to 500 cases/day. The accumulative cases vary from one country to another during the armed conflict. The highest cumulative number of cases were reported in Libya, Syria and Yemen.Conclusions: Our analysis demonstrates that the armed conflict provided an opportunity for SARS-CoV-2 to spread. The early weeks of the pandemic coincided with the most intense period of the armed conflicts, and few cases were officially reported. This indicates undercounting and hidden spread during the early stage of the pandemic. The pandemic then spread dramatically as the armed conflict declined, reaching its greatest spread by December 2020. Full-blown transmission of the COVID-19 pandemic in these countries is expected. Therefore, urgent national and international strategies should be implemented to combat the pandemic and its consequences.

The Amplifying Effect of Conflicts on Case Fatality Rate of COVID-19: Evidence From 120 Countries

“…These results suggest that the mortality risk of COVID-19 will increase because of the escalation in conflicts. Our findings are consistent with the recent study by Daw ( 7 ) that links higher armed conflict levels to the greater spread of the COVID-19 pandemic in Libya, Syria, and Yemen. Future articles can use different indicators and econometric techniques using survey data to predict the drivers of the spread of the COVID-19 pandemic and the CFR in different countries.…”

“…Similarly, Moosa and Khatatbeh ( 6 ) found that age structure and population density are the main determinants of the CFR. Daw ( 7 ) showed that armed conflict is the main determinant of the spread of COVID-19 in Libya, Syria, and Yemen. Elgar et al ( 8 ) indicated that social capital and income inequality are the main drivers of COVID-19 deaths in 84 countries.…”

Stochastic Dynamics of the COVID-19 Case-Fatality Ratios in Indonesia, Malaysia, and the Philippines: Economic Implications for the Post-COVID-19 Era

“…Note that when we focus on the first difference of the series, all CFR values become stationary. The results from Malaysia, which show the predictability of the CFR values, are in line with the findings of Diaz et al ( 7 ), Sorci et al ( 9 ), Daw ( 10 ), Zhai et al ( 11 ), Khan et al ( 12 ), and Hradsky and Komarek ( 13 ). However, the findings from Indonesia and the Philippines, which provide the unpredictability of the CFR values, are in line with the previous evidence in Ioannidis et al ( 5 ).…”

“…Moreover, Daw ( 10 ) shows that the conflicts raise the CFR values in Libya, Syria, and Yemen. Zhai et al ( 11 ) further develop this evidence by using the cross-section data from 120 countries.…”

“…Zhai et al ( 11 ) further develop this evidence by using the cross-section data from 120 countries. Daw ( 10 ) and Zhai et al ( 11 ) conclude that conflicts are the main variables determining the CFR. Khan et al ( 12 ) also observe that the CFR of the COVID-19 is negatively related to the efficiency of government, civil society, and health expenditures using the dataset of 86 countries.…”