The Abbott Pandemic Defense Coalition: a unique multisector approach adds to global pandemic preparedness efforts

Mayaro Virus as the cause of Acute Febrile Illness in the Colombian Amazon Basin

Introduction

Mayaro Fever (MF) is a tropical disease caused by the Mayaro virus (MAYV), with outbreaks documented in Latin America.

Methods

A hospital-based fever surveillance in Leticia, Colombian Amazon, collected sera from 1,460 patients aged 5-89 between December 2020 and April 2023.

Results

Dengue and malaria were the main diagnoses (19.4 and 5.8%, respectively), leaving 71.4% of cases unidentified after testing. Metagenomic sequencing and real-time RT-qPCR testing identified MAYV in two patients (25-year-old male and an 80-year-old female) exhibiting typical symptoms, of MF including rash, joint pain, and fever. Phylogenetics analysis of these two viruses revealed a close relationship to Peruvian strains within the MAYV D genotype.

Discussion

The study of AFI in Leticia, Colombia, identified dengue as prevalent, with malaria, COVID-19, Influenza, and Zika viruses also detected. Despite extensive testing, most cases remained unexplained until metagenomic sequencing revealed MAYV, previously unseen in Colombia but known in neighboring countries.

Conclusion

This study presents the first near full-length genomes of MAYV in Colombia, highlighting the need for further seroprevalence studies and enhanced surveillance to understand and control the spread of the virus in the region.

Next-generation sequencing survey of acute febrile illness in Senegal (2020-2022)

Introduction

Acute febrile illnesses (AFI) in developing tropical and sub-tropical nations are challenging to diagnose due to the numerous causes and non-specific symptoms. The proliferation of rapid diagnostic testing and successful control campaigns against malaria have revealed that non-Plasmodium pathogens still contribute significantly to AFI burden. Thus, a more complete understanding of local trends and potential causes is important for selecting the correct treatment course, which in turn will reduce morbidity and mortality. Next-generation sequencing (NGS) in a laboratory setting can be used to identify known and novel pathogens in individuals with AFI.

Methods

In this study, plasma was collected from 228 febrile patients tested negative for malaria at clinics across Senegal from 2020-2022. Total nucleic acids were extracted and converted to metagenomic NGS libraries. To identify viral pathogens, especially those present at low concentration, an aliquot of each library was processed with a viral enrichment panel and sequenced. Corresponding metagenomic libraries were also sequenced to identify non-viral pathogens.

Results and Discussion

Sequencing reads for pathogens with a possible link to febrile illness were identified in 51/228 specimens, including (but not limited to): Borrelia crocidurae (N = 7), West Nile virus (N = 3), Rickettsia felis (N = 2), Bartonella quintana (N = 1), human herpesvirus 8 (N = 1), and Saffold virus (N = 1). Reads corresponding to Plasmodium falciparum were detected in 19 specimens, though their presence in the cohort was likely due to user error of rapid diagnostic testing or incorrect specimen segregation at the clinics. Mosquito-borne pathogens were typically detected just after the conclusion of the rainy season, while tick-borne pathogens were mostly detected before the rainy season. The three West Nile virus strains were phylogenetically characterized and shown to be related to both European and North American clades. Surveys such as this will increase the understanding of the potential causes of non-malarial AFI, which may help inform diagnostic and treatment options for clinicians who provide care to patients in Senegal.

Development and Validation of Three Automated High-Throughput Molecular Tests to Detect Monkeypox Virus Infections

BACKGROUND

The 2022 outbreak of the clade IIb monkeypox virus and subsequent global spread lead to an urgent need for the development of high-throughput, sensitive, and reproducible diagnostic tests.

METHODS

We developed 3 assays to detect monkeypox virus, 2 (MPXV+ and MPXV) for m2000 RealTime and 1 (MPXV) for Alinity m platforms. Dual targets in E9L and B6R (MPXV+) and J2L and B7R (MPXV) increased mutation resistance. In silico prediction indicates MPXV+ cross-reactivity with orthopox viruses and specific monkeypox virus detection with MPXV.

RESULTS

m2000 RealTime MPXV+ and MPXV assay sensitivity was determined to be 3.2 plaque-forming units/mL using a reference virus culture diluted into universal transport medium (UTM). Alinity m MPXV lower limit of detection was 200 copies/mL using monkeypox virus plasmids in pooled UTM matrix. m2000 RealTime MPXV+ and MPXV assays were validated with lesion swabs in UTM and 1:1 saliva to UTM mixtures. Commercially available and remnant clinical lesion specimens in UTM were tested with RealTime MPXV+, RealTime MPXV and Alinity m MPXV assays and demonstrated high agreement to known mpox (MPX)-positive specimens.

CONCLUSIONS

RealTime MPXV+, RealTime MPXV, and Alinity MPXV are high throughput and sensitive assays used for the detection of monkeypox virus. These assays maybe useful during MPX outbreaks.

COVID-19 waves in an urban setting 2020-2022: an electronic medical record analysis

Background

Global and national surveillance efforts have tracked COVID-19 incidence and clinical outcomes, but few studies have compared comorbid conditions and clinical outcomes across each wave of the pandemic. We analyzed data from the COVID-19 registry of a large urban healthcare system to determine the associations between presenting comorbidities and clinical outcomes during the pandemic.

Methods

We analyzed registry data for all inpatients and outpatients with COVID-19 from March 2020 through September 2022 (N = 44,499). Clinical outcomes were death, hospitalization, and intensive care unit (ICU) admission. Demographic and clinical outcomes data were analyzed overall and for each wave. Unadjusted and multivariable logistic regressions were performed to explore the associations between age, sex, race, ethnicity, comorbidities, and mortality.

Results

Waves 2 and 3 (Alpha and Delta variants) were associated with greater hospitalizations, ICU admissions, and mortality than other variants. Chronic pulmonary disease was the most common comorbid condition across all age groups and waves. Mortality rates were higher in older patients but decreased across all age groups in later waves. In every wave, mortality was associated with renal disease, congestive heart failure, cerebrovascular disease, diabetes, and chronic pulmonary disease. Multivariable analysis found that liver disease and renal disease were significantly associated with mortality, hospitalization, and ICU admission, and diabetes was significantly associated with hospitalization and ICU admission.

Conclusion

The COVID-19 registry is a valuable resource to identify risk factors for clinical outcomes. Our findings may inform risk stratification and care planning for patients with COVID-19 based on age and comorbid conditions.

Metagenomic Detection of Divergent Insect- and Bat-Associated Viruses in Plasma from Two African Individuals Enrolled in Blood-Borne Surveillance

Metagenomic next-generation sequencing (mNGS) has enabled the high-throughput multiplexed identification of sequences from microbes of potential medical relevance. This approach has become indispensable for viral pathogen discovery and broad-based surveillance of emerging or re-emerging pathogens. From 2015 to 2019, plasma was collected from 9586 individuals in Cameroon and the Democratic Republic of the Congo enrolled in a combined hepatitis virus and retrovirus surveillance program. A subset (n = 726) of the patient specimens was analyzed by mNGS to identify viral co-infections. While co-infections from known blood-borne viruses were detected, divergent sequences from nine poorly characterized or previously uncharacterized viruses were also identified in two individuals. These were assigned to the following groups by genomic and phylogenetic analyses: densovirus, nodavirus, jingmenvirus, bastrovirus, dicistrovirus, picornavirus, and cyclovirus. Although of unclear pathogenicity, these viruses were found circulating at high enough concentrations in plasma for genomes to be assembled and were most closely related to those previously associated with bird or bat excrement. Phylogenetic analyses and in silico host predictions suggested that these are invertebrate viruses likely transmitted through feces containing consumed insects or through contaminated shellfish. This study highlights the power of metagenomics and in silico host prediction in characterizing novel viral infections in susceptible individuals, including those who are immunocompromised from hepatitis viruses and retroviruses, or potentially exposed to zoonotic viruses from animal reservoir species.