BackgroundThe burden of COVID-19 in low-income and conflict-affected countries remains unclear, largely reflecting low testing rates. In parts of Yemen, reports indicated a peak in hospital admissions and burials during May–June 2020. To estimate excess mortality during the epidemic period, we quantified activity across all identifiable cemeteries within Aden governorate (population approximately 1 million) by analysing very high-resolution satellite imagery and compared estimates to Civil Registry office records.MethodsAfter identifying active cemeteries through remote and ground information, we applied geospatial analysis techniques to manually identify new grave plots and measure changes in burial surface area over a period from July 2016 to September 2020. After imputing missing grave counts using surface area data, we used alternative approaches, including simple interpolation and a generalised additive mixed growth model, to predict both actual and counterfactual (no epidemic) burial rates by cemetery and across the governorate during the most likely period of COVID-19 excess mortality (from 1 April 2020) and thereby compute excess burials. We also analysed death notifications to the Civil Registry office over the same period.ResultsWe collected 78 observations from 11 cemeteries. In all but one, a peak in daily burial rates was evident from April to July 2020. Interpolation and mixed model methods estimated ≈1500 excess burials up to 6 July, and 2120 up to 19 September, corresponding to a peak weekly increase of 230% from the counterfactual. Satellite imagery estimates were generally lower than Civil Registry data, which indicated a peak 1823 deaths in May alone. However, both sources suggested the epidemic had waned by September 2020.DiscussionTo our knowledge, this is the first instance of satellite imagery being used for population mortality estimation. Findings suggest a substantial, under-ascertained impact of COVID-19 in this urban Yemeni governorate and are broadly in line with previous mathematical modelling predictions, though our method cannot distinguish direct from indirect virus deaths. Satellite imagery burial analysis appears a promising novel approach for monitoring epidemics and other crisis impacts, particularly where ground data are difficult to collect.

Abstract. We analyzed surveillance data of a dengue outbreak (2010) reported to the Hadramout Health Office (Yemen) and retrospectively analyzed dengue-related epidemiological and entomological events reported in Hadramout from 2005 to 2009. A total of 630 immunoglobulin M (IgM) -confirmed dengue cases of 982 febrile cases was reported during the period from February to June of 2010; 12 cases died, giving case fatality a rate of 1.9%. Among febrile cases, the highest proportion of dengue cases (37.3%) was reported in the 15-to 24-year-old age group. The overall attack rate was 0.89/1,000. The average number of cases reported by month over the preceding 5-year period compared with the 2010 data is consistent with endemicity of dengue in the region and supports epidemic designation for the dengue activity in 2010. Recognition of endemic dengue transmission and potential for substantial dengue epidemics highlight the need for consistent laboratory-based surveillance that can support prevention and control activities accordingly.

Introduction: Although the government of Yemen changed the national policy for treating malaria in November 2005 from chloroquine to

(ENGLISH) Background The burden of COVID-19 in low-income and conflict-affected countries is still unclear, largely reflecting low testing rates. In parts of Yemen, reports indicated a peak in hospital admissions and burials during May-June 2020. To estimate excess mortality during the epidemic period, we quantified activity across all identifiable cemeteries within Aden governorate in Yemen (population approximately one million) by analysing very high-resolution satellite imagery, and compared estimates to Civil Registry office records from the city. Methods After identifying active cemeteries through remote and ground information, we applied geospatial analysis techniques to manually identify new grave plots and measure changes in burial surface area over a period from July 2016 to September 2020. After imputing missing grave counts using surface area data, we used alternative approaches, including simple interpolation and a generalised additive mixed growth model, to predict both actual and counterfactual (no epidemic) burial rates by cemetery and across the governorate during the most likely period of COVID-19 excess mortality (from 1 April 2020), and thereby compute excess burials. We also analysed death notifications to the Civil Registry office during April-July 2020 and in previous years. Results We collected 78 observations from 11 cemeteries, of which 10 required imputation from burial surface area. Cemeteries ranged in starting size from 0 to 6866 graves. In all but one a peak in daily burial rates was evident from April to July 2020. Interpolation and mixed model methods estimated ≈ 1500 excess burials up to 6 July, and 2120 up to 19 September, corresponding to a peak weekly increase of 230% from the counterfactual. Satellite imagery estimates were generally lower than Civil Registry data, which indicated a peak 1823 deaths in May alone. However, both sources suggested the epidemic had waned by September 2020. Discussion To our knowledge this is the first instance of satellite imagery being used for population mortality estimation. Findings suggest a substantial, under-ascertained impact of COVID-19 in this urban Yemeni governorate, and are broadly in line with previous mathematical modelling predictions, though our method cannot distinguish direct from indirect virus deaths. Satellite imagery burial analysis appears a promising novel approach for monitoring epidemics and other crisis impacts, particularly where ground data are difficult to collect.

A cross-sectional study was conducted during the period of August 2007-April 2008 at Al-Wahda Teaching Hospital in Yemen to investigate prevalence and risk factors for placental malaria and anaemia and their effects on birthweight. Sociodemographic characteristics were gathered, maternal haemoglobin was measured and blood films were examined for malaria. Newborn birthweight was recorded. Out of 900 parturient women, malaria blood films were positive in 32 (3.6%) cases: in six sets of peripheral, placental and cord samples; in 15 placental and cord samples; and in 11 placental samples only. Malaria was not associated with age and parity, but it was significantly associated with history of fever [odds ratio (OR) 8.5, 95% CI 3.7-19, P<0.001], rural residence (OR 2.5, 95% CI 1.1-5.3, P=0.01) and rainy season (OR 5.1, 95% CI 1.7-15.2, P=0.003). Overall, 694 (77.1%) out of these 900 women had anaemia (Hb<11g/dl) and 16 (1.8%) patients had severe anaemia (Hb<7g/dl). Anaemia was not associated with age, parity and malaria. Low birthweight was significantly associated with malaria (OR 5.7, 95% CI 1.7-18.5; P=0.004). Thus, preventive measures (bednets and intermittent preventive treatment) should be employed for pregnant women regardless of their age or parity.