Association between air raids and reported incidence of cholera in Yemen, 2016-19: an ecological modelling study

BACKGROUND

Yemen continues to endure cholera outbreaks during ongoing conflict and destructive environmental events. Air raids have been used throughout the conflict to target military and civilian infrastructure. We aimed to assess the association between air raids and cholera incidence while taking into account geographical, environmental, economic, and demographic factors that drive outbreaks.

METHODS

In this ecological modelling study, we used data from Sept 12, 2016, to Dec 29, 2019, for the number of air raids, vegetation coverage, surface water, precipitation, temperature, economic variables, and cholera case and population data to model the association between conflict and the weekly incidence of cholera (per 100 000 people) in Yemen. Data were transformed into weekly intervals and governorates were categorised according to air raid severity (the number of raids in the previous 3 months). We used a negative binomial generalised additive model that accounted for geographical location and environmental, temporal, economic, and demographic variables to estimate incidence rate ratios for the association between air raid severity and cases of cholera.

FINDINGS

During the study period, 2 107 912 cases of cholera were reported in Yemen, and a minimum of 11 366 air raids were recorded. After controlling for relevant factors, compared with no air raids, all other levels of air raid severity were significantly associated with cholera incidence. The largest effect was noted in governorates with severe air raid levels (ie, ≥76 during the previous 3 months), which had an incidence rate ratio of 2·06 (95% CI 1·59-2·69; p<0·0001) for cholera compared with governorates with no air raids in the previous 3 months. Economic factors were also significantly associated with increased cholera incidence.

INTERPRETATION

Air raids were significantly associated with the burden of cholera in Yemen, even after controlling for other relevant factors. Quantification of this relationship further shows that the cholera outbreak is largely a result of human action rather than a natural occurrence, and demonstrates the conflict's devastating effects on health. Our findings highlight the need for ceasefire and peacebuilding efforts, as well as infrastructure and economic restoration, to reduce Yemen's cholera burden.

FUNDING

None.

TRANSLATION

For the Arabic translation of the abstract see Supplementary Materials section.

Assessing Antimicrobial Resistance, Utilization, and Stewardship in Yemen: An Exploratory Mixed-Methods Study

Antimicrobial resistance (AMR), largely driven by irrational use of antimicrobials, is a global, multifaceted problem calling for a complete understanding of all contributory factors for effective containment. In conflict settings, war-wounds and malnutrition can combine with existing social determinants to increase demand for antibiotics, compounding irrational use. In this study, we focus on Yemen, a low-income country with active conflict for the last 5 years, and analyze the current status of awareness and stewardship efforts regarding AMR. We performed a survey of prescribers/physicians and pharmacists to describe perceptions of AMR prevalence, antibiotic use practices, and stewardship in Yemen, supported by a nonsystematic scoping literature review and a key informant interview. Participants (96%, N = 54) reported a perceived high AMR prevalence rate. Prescribers (74%, 20/27) reported pressure to prescribe broad-spectrum antibiotics. In the majority of cases (81%, 22/27), antimicrobial sensitivity tests (AST) were not performed to inform antibiotic choice. The main barrier to AST was cost. Most pharmacists (67%, 18/27) sold antibiotics without prescriptions. Amoxicillin (including amoxicillin-clavulanate) was the most-commonly prescribed (63%, 17/27) or dispensed (81%, 22/27) antibiotic. AST was rated the least important solution to AMR in Yemen. While there was awareness of a high AMR rate, stewardship is poor in Yemen. We note that barriers to the use of AST could be addressed through the deployment of reliable, affordable, quality rapid diagnostics, and AST kits. Compulsory continuing education emphasizing the use of AST to guide prescribing and patients' awareness programs could help avoid irrational use.

A mathematical model to estimate the incidence of child wasting in Yemen

INTRODUCTION

The ongoing civil war in Yemen has severely restricted imports of food and fuel, disrupted livelihoods and displaced millions, worsening already high pre-war levels of food insecurity. Paired with frequent outbreaks of disease and a collapsed health system, this has brought rates of wasting in children under five to the country's highest recorded levels, which continue to increase as the crisis worsens and aid becomes increasingly limited. In their planning of services to treat and prevent wasting in children, humanitarian agencies rely on a standard calculation to estimate the expected number of cases for the coming year, where incidence is estimated from prevalence and the average duration of an episode of wasting. The average duration of an episode of moderate and severe wasting is currently estimated at 7.5 months-a globally-used value derived from historical cohort studies. Given that incidence varies considerably by context-where food production and availability, treatment coverage and disease rates all vary-a single estimate cannot be applied to all contexts, and especially not a highly unstable crisis setting such as Yemen. While recent studies have aimed to derive context-specific incidence estimates in several countries, little has been done to estimate the incidence of both moderate and severe wasting in Yemen.

METHODS

In order to provide context-specific estimates of the average duration of an episode, and resultingly, incidence correction factors for moderate and severe wasting, we have developed a Markov model. Model inputs were estimated using a combination of treatment admission and outcome records compiled by the Yemen Nutrition Cluster, 2018 and 2019 SMART surveys, and other estimates from the literature. The model derived estimates for the governorate of Lahj, Yemen; it was initialized using August 2018 SMART survey prevalence data and run until October 2019-the date of the subsequent SMART survey. Using a process of repeated model calibration, the incidence correction factors for severe wasting and moderate wasting were found, validating the resulting prevalence against the recorded value from the 2019 SMART survey.

RESULTS

The average durations of an episode of moderate and severe wasting were estimated at 4.86 months, for an incidence correction factor k of 2.59, and 3.86 months, for an incidence correction factor k of 3.11, respectively. It was found that the annual caseload of moderate wasting was 36% higher and the annual caseload of severe wasting 58% higher than the originally-assumed values, estimated with k = 1.6.

CONCLUSION

The model-derived incidence rates, consistent with findings from other contexts that a global incidence correction factor cannot be sufficient, allow for improved, context-specific estimates of the burden of wasting in Yemen. In crisis settings such as Yemen where funding and resources are extremely limited, the model's outputs holistically capture the burden of wasting in a way that may guide effective decision-making and may help ensure that limited resources are allocated most effectively.

Forms of Health System Fragmentation During Conflict: The Case of Yemen

The continuous and protracted conflict in Yemen has evolved into the worst humanitarian situation in modern history. All public structures in the country, including the health system and its basic functions, have been under tremendous pressures. One of the key obstacles to improve the health outcomes in Yemen is fragmentation of the health system. This study aims at exploring and documenting the forms of health system fragmentation in humanitarian and conflict-affected contexts by studying Yemen as a case study. We collected national qualitative data from key informants through in-depth interviews. A pool of respondents was identified from the Ministry of Public Health and Population, donors, and non-governmental organizations. Data were collected between May and June 2019. We interviewed eight key informants and reviewed national health policy documents, and references provided by key informants. Interviews were recorded, transcribed, and analyzed using qualitative content analysis. We further conducted a literature review to augment and triangulate the findings. Six themes emerged from our datasets and analyses, representing various forms of fragmentation: political, structural, inter-sectoral, financial, governance, and health agenda-related forms. Health system fragmentation in Yemen existed before the conflict eruption and has aggravated as the conflict evolves. The humanitarian situation and the collapsing health system enabled the influx of various national and international health actors. In conclusion, the protracted conflict and fragile situation in Yemen have accentuated the fragmentation of the health system. Addressing these fragmentations' forms by all health actors and building consensus on health system agenda are recommended. Health system analysis and in-depth study of fragmentation drivers in Yemen can be beneficial to build common ground and priorities to reduce health system fragmentation. Furthermore, capacity building of a health system is fundamental for the humanitarian development nexus, health system integration, and recovery efforts in the future.

COVID-19 in Conflict: The devastating impact of withdrawing humanitarian support on universal health coverage in Yemen

The authors warn that, in the context of Yemen, the closure of humanitarian lifesaving programmes and shifting support toward health security, i.e. to support COVID-19 response, at the expense of primary health care support, will undermine existing health system strengthening efforts, worsen the humanitarian crisis and will accentuate the impact of COVID-19. The authors urge the international community and the Government of Yemen to carefully consider a more comprehensive approach to support Yemen's COVID-19 response while maintaining, and strengthening, essential public health services.

A predictive model for healthcare coverage in Yemen

Introduction

The ongoing war in Yemen continues to pose challenges for healthcare coverage in the country especially with regards to critical gaps in information systems needed for planning and delivering health services. Restricted access to social services including safe drinking water and sanitation systems have likely led to an increase in the spread of diarrheal diseases which remains one of greatest sources of mortality in children under 5 years old. To overcome morbidity and mortality from diarrheal diseases among children in the context of severe information shortages, a predictive model is needed to determine the burden of diarrheal disease on Yemeni children and their ability to reach curative health services through an estimate of healthcare coverage. This will allow for national and local health authorities and humanitarian partners to make better informed decisions for planning and providing health care services.

Methods

A probabilistic Markov model was developed based on an analysis of Yemen’s health facilities’ clinical register data provided by UNICEF. The model combines this health system data with environmental and conflict-related factors such as the destruction of infrastructure (roads and health facilities) to fill in gaps in population-level data on the burden of diarrheal diseases on children under five, and the coverage rate of the under-five sick population with treatment services at primary care facilities. The model also provides estimates of the incidence rate, and treatment outcomes including treatment efficacy and mortality rate.

Results

By using alternatives to traditional healthcare data, the model was able to recreate the observed trends in treatment with no significant difference compared to provided validation data. Once validated, the model was used to predict the percent of sick children with diarrhea who were able to reach, and thus receive, treatment services (coverage rate) for 2019 which ranged between an average weekly minimum of 1.73% around the 28th week of the year to a weekly maximum coverage of just over 5% around the new year. These predictions can be translated into policy decisions such as when increased efforts are needed to reach children and what type of service delivery modalities may be the most effective.

Conclusion

The model developed and presented in this manuscript shows a seasonal trend in the spread of diarrheal disease in children under five living in Yemen through a novel incorporation of weather, infrastructure and conflict parameters in the model. Our model also provides new information on the number of children seeking treatment and how this is influenced by the ongoing conflict. Despite the work of the national and local health authorities with the support of aid organizations, during the mid-year rains up to 98% of children with diarrhea are unable to receive treatment services. Thus, it is recommended that community outreach or other delivery modalities through which services are delivered in closer proximity to those in need should be scaled up prior to and during these periods. This would serve to increase number of children able to receive treatment by lessening the prohibitive travel burden, or access constraint, on families during these times.