Strengthening laboratories in response to outbreaks in humanitarian emergencies and conflict settings: Results, challenges and lessons from expanding PCR diagnostic capacities for COVID-19 testing in Yemen.

BACKGROUND: When the COVID-19 pandemic was declared, Yemen, a country facing years of conflict had only one laboratory with PCR testing capacity. In this article, we describe the outcome of the implementation of molecular based diagnostics platform in Yemen and highlight the key milestones the country went through to increase access to testing for its populations residing in a geographically vast and politically divided country. METHODS: A retrospective assessment of COVID-19 laboratory response activities was done detailing the needs assessment process, timelines, geographical coverage, and outcomes of the activities. Laboratory data was analyzed to construct the geographical locations of COVID-19 testing laboratories and the numbers of tests performed in each facility to highlight the demands of testing for travelers. Finally, we discuss the impact these activities had in enabling the movement of people across international borders for economic gains and in delivery of critical humanitarian aid. OUTCOME: PCR testing capacities in Yemen significantly improved, from one laboratory in Sanaa in April 2020 to 18 facilities across the country by June 2022. In addition, the number of functional Real-Time PCR thermocyclers increased from one to 32, the PCR tests output per day improved from 192 to 6144 tests per day. Results from analysis of laboratory data showed there were four peaks of COVID-19 in Yemen as October 2022. The majority of laboratory tests were performed for travelers than for medical or public health reasons. Demand for laboratory testing in Yemen was generally low and waned over time as the perceived risk of COVID-19 declined, in parallel with rollout of the COVID-19 vaccines. DISCUSSION/CONCLUSION: The successful expansion of laboratory testing capacity was instrumental in the control and management of COVID-19 cases and critical in the implementation of public response strategies, including restrictions on gathering. Laboratory testing also facilitated the movement of humanitarian agencies and delivery of aid and enabled hundreds of thousands of Yemeni nationals to travel internationally. By virtue of these outcomes, the impact of laboratory strengthening activities was thus felt in the health sector and beyond.

Genomic epidemiology reveals multidrug resistant plasmid spread between Vibrio cholerae lineages in Yemen.

Since 2016, Yemen has been experiencing the largest cholera outbreak in modern history. Multidrug resistance (MDR) emerged among Vibrio cholerae isolates from cholera patients in 2018. Here, to characterize circulating genotypes, we analysed 260 isolates sampled in Yemen between 2018 and 2019. Eighty-four percent of V. cholerae isolates were serogroup O1 belonging to the seventh pandemic El Tor (7PET) lineage, sub-lineage T13, whereas 16% were non-toxigenic, from divergent non-7PET lineages. Treatment of severe cholera with macrolides between 2016 and 2019 coincided with the emergence and dominance of T13 subclones carrying an incompatibility type C (IncC) plasmid harbouring an MDR pseudo-compound transposon. MDR plasmid detection also in endemic non-7PET V. cholerae lineages suggested genetic exchange with 7PET epidemic strains. Stable co-occurrence of the IncC plasmid with the SXT family of integrative and conjugative element in the 7PET background has major implications for cholera control, highlighting the importance of genomic epidemiological surveillance to limit MDR spread.

The first 2 months of the SARS-CoV-2 epidemic in Yemen: Analysis of the surveillance data.

INTRODUCTION: Yemen was one of the last countries in the world to declare the first case of the pandemic, on 10 April 2020. Fear and concerns of catastrophic outcomes of the epidemic in Yemen were immediately raised, as the country is facing a complex humanitarian crisis. The purpose of this report is to describe the epidemiological situation in Yemen during the first 2 months of the SARS-CoV-2 epidemic. METHODS: We analyzed the epidemiological data from 18 February to 05 June 2020, including the 2 months before the confirmation of the first case. We included in our analysis the data from 10 out of 23 governorates of Yemen, located in southern and eastern part of the country. RESULTS: A total of 469 laboratory confirmed, 552 probable and 55 suspected cases with onset of symptoms between 18 February and 5 June 2020 were reported through the surveillance system. The median age among confirmed cases was 46 years (range: 1-90 years), and 75% of the confirmed cases were male. A total of 111 deaths were reported among those with confirmed infection. The mean age among those who died was 53 years (range: 14-88 years), with 63% of deaths (n = 70) occurring in individuals under the age 60 years. A total of 268 individuals with confirmed SARS-CoV-2 infection were hospitalized (57%), among whom there were 95 in-hospital deaths. CONCLUSIONS: The surveillance strategy implemented in the first 2 months of the SARS CoV 2 in the southern and eastern governorates of Yemen, captured mainly severe cases. The mild and moderate cases were not self-reported to the health facilities and surveillance system due to limited resources, stigma, and other barriers. The mortality appeared to be higher in individuals aged under 60 years, and most fatalities occurred in individuals who were in critical condition when they reached the health facilities. It is unclear whether the presence of other acute comorbidities contributed to the high death rate among SARS-CoV-2 cases. The findings only include the southern and eastern part of the country, which is home to 31% of the total population of Yemen, as the data from the northern part of the country was inaccessible for analysis. This makes our results not generalizable to the rest of the country.

Targeting remaining pockets of malaria transmission in Kenya to hasten progress towards national elimination goals: an assessment of prevalence and risk factors in children from the Lake endemic region.

BACKGROUND: With an overall decline of malaria incidence, elimination of malaria is gradually becoming the next target for many of countries affected by the disease. In Kenya the national malaria control strategy is aiming to reach pre-elimination for most parts of the country. However, considerable heterogeneity in prevalence of the disease within the country and especially the remaining high prevalent region of the Lake endemic region is likely to slow progress towards this target. To achieve a sustained control and an eventual elimination, a clear understanding of drivers of ongoing malaria transmission in remaining hotspots is needed. METHODS: Data from the 2015 Malaria Indicator Survey (MIS) were analysed for prevalence of malaria parasitaemia in children (6 months to 14 years) of different countries within the highly endemic Lake region. Univariate and multivariate logistic regression analysis were preformed to explore associations between selected risk factors and being parasitaemic. A predictive model was built for the association between malaria and the risk factors with the aim of identifying heterogeneities of the disease at the lower administrative levels. RESULTS: Overall, 604/2253 (27%, 95% CI 21.8-32.2) children were parasitaemic. The highest prevalence was observed in Busia County (37%) and lowest in Bungoma County (18%). Multivariate logistic regression analysis showed that the 10-14 years age group (OR = 3.0, 95% CI 2.3-4.1), households in the poorest socio-economic class (OR = 2.1, 95% CI 1.3-3.3), farming (OR = 1.4, 95% CI 1.2-2.5) and residence in Busia (OR = 4.6, 95% CI 2.1-8.2), Kakamega (OR = 2.6, 95% CI 1.3-5.4), and Migori counties (OR = 4.6 95% CI 2.1-10.3) were associated with higher risk of parasitaemia. Having slept under a long-lasting insecticide-treated bed net (LLIN) was associated with a lower risk (OR = 0.7, 95% CI 0.6-0.9). No association were found between malaria infection and the gender of the child, the household head, and the education status of the household head. DISCUSSION AND CONCLUSION: Detailed analysis of malaria prevalence data in a hotspot area can identify new threats and avail opportunities for directing intervention. In the Lake endemic region of Kenya, interventions should be focused more on counties with the highest prevalence, and should target older children as well as children from the lower socio-economic strata. Precisely targeting interventions in remaining hotspots and high-risk populations will likely make impact and accelerate progress towards pre-elimination targets.

Comparison of PfHRP-2/pLDH ELISA, qPCR and microscopy for the detection of plasmodium events and prediction of sick visits during a malaria vaccine study.

BACKGROUND: Compared to expert malaria microscopy, malaria biomarkers such as Plasmodium falciparum histidine rich protein-2 (PfHRP-2), and PCR provide superior analytical sensitivity and specificity for quantifying malaria parasites infections. This study reports on parasite prevalence, sick visits parasite density and species composition by different diagnostic methods during a phase-I malaria vaccine trial. METHODS: Blood samples for microscopy, PfHRP-2 and Plasmodium lactate dehydrogenase (pLDH) ELISAs and real time quantitative PCR (qPCR) were collected during scheduled (n = 298) or sick visits (n = 38) from 30 adults participating in a 112-day vaccine trial. The four methods were used to assess parasite prevalence, as well as parasite density over a 42-day period for patients with clinical episodes. RESULTS: During scheduled visits, qPCR (39.9%, N = 119) and PfHRP-2 ELISA (36.9%, N = 110) detected higher parasite prevalence than pLDH ELISA (16.8%, N = 50) and all methods were more sensitive than microscopy (13.4%, N = 40). All microscopically detected infections contained P. falciparum, as mono-infections (95%) or with P. malariae (5%). By qPCR, 102/119 infections were speciated. P. falciparum predominated either as monoinfections (71.6%), with P. malariae (8.8%), P. ovale (4.9%) or both (3.9%). P. malariae (6.9%) and P. ovale (1.0%) also occurred as co-infections (2.9%). As expected, higher prevalences were detected during sick visits, with prevalences of 65.8% (qPCR), 60.5% (PfHRP-2 ELISA), 21.1% (pLDH ELISA) and 31.6% (microscopy). PfHRP-2 showed biomass build-up that climaxed (1813±3410 ng/mL SD) at clinical episodes. CONCLUSION: PfHRP-2 ELISA and qPCR may be needed for accurately quantifying the malaria parasite burden. In addition, qPCR improves parasite speciation, whilst PfHRP-2 ELISA is a potential predictor for clinical disease caused by P. falciparum. TRIAL REGISTRATION: ClinicalTrials.gov NCT00666380.