Mapping Potential Amplification and Transmission Hotspots for MERS-CoV, Kenya

Spatial examination of social and environmental drivers of Middle East respiratory syndrome coronavirus (MERS-CoV) across Kenya

Climate and agricultural land-use change has increased the likelihood of infectious disease emergence and transmissions, but these drivers are often examined separately as combined effects are ignored. Further, seldom are the influence of climate and agricultural land use on emerging infectious diseases examined in a spatially explicit way at regional scales. Our objective in this study was to spatially examine the climate, agriculture, and socio-demographic factors related to agro-pastoralism, and especially the combined effects of these variables that can influence the prevalence of Middle East respiratory syndrome coronavirus (MERS-CoV) in dromedary camels across northern Kenya. Our research questions focused on: (1) How MERS-CoV in dromedary camels has varied across geographic regions of northern Kenya, and (2) what climate, agriculture, and socio-demographic factors of agro-pastoralism were spatially related to the geographic variation of MERS-CoV cases in dromedary camels. To answer our questions, we analyzed the spatial distribution of historical cases based on serological evidence of MERS-CoV at the county level and applied spatial statistical analysis to examine the spatial relationships of the MERS-CoV cases between 2016 and 2018 to climate, agriculture, and socio-demographic factors of agro-pastoralism. Regional differences in MERS-CoV cases were spatially correlated with both social and environmental factors, and particularly ethno-religious camel practices, which highlight the complexity in the distribution of MERS-CoV in dromedary camels across Kenya.

Biphasic MERS-CoV Incidence in Nomadic Dromedaries with Putative Transmission to Humans, Kenya, 2022-2023

Middle East respiratory syndrome coronavirus (MERS-CoV) is endemic in dromedaries in Africa, but camel-to-human transmission is limited. Sustained 12-month sampling of dromedaries in a Kenya abattoir hub showed biphasic MERS-CoV incidence; peak detections occurred in October 2022 and February 2023. Dromedary-exposed abattoir workers (7/48) had serologic signs of previous MERS-CoV exposure.

Knowledge, attitudes, and practices on camel respiratory diseases and conditions in Garissa and Isiolo, Kenya

Background

Livestock farmers' attitudes, practices, and behaviors are major factors in infection prevention and control of animal diseases. Kenya has the fourth largest global camel population, and the industry has grown over the last two decades, transforming beyond the traditional camel-keeping areas to include peri-urban camel trade and value chain growth. The dromedary camel is resilient, and it is a preferred species in the arid and semi-arid areas (ASALs) of Kenya. However, it still faces many health and production challenges; to identify infection drivers and risky behaviors for camel respiratory illnesses and conditions in Kenya, we conducted a knowledge, attitudes, and practices (KAP) survey.

Method

Using a set of tools (questionnaires, key informant interviews, and focus group discussions), we interviewed camel owners, herders, agro-veterinary outlets, and other relevant value chain stakeholders in Garissa and Isiolo counties (n = 85). Data were analyzed using descriptive and analytic statistics.

Results

Most camel owners/herders are male and most are relatively uneducated (85.5%). The camels were used primarily for milk and meat production, income generation, and transport. Larger herd sizes (>30 camels) and owner/herder's lack of formal education are risk factors for owner-reported respiratory illnesses in camels. Major clinical signs of respiratory conditions were coughing (85.7%), nasal discharge (59.7%), and fever (23.4%). Diseases, lack of feeds, theft, and marketing challenges are the major constraints to camel production in Kenya. Owners-herders use drugs indiscriminately and this may contribute to antimicrobial resistance challenges.

Conclusion

Practitioners in the camel value chain want more commitment from the government and animal health officials on support services and access to veterinary services. Watering points, grazing areas, and marketing points are the primary areas for congregating camels and have a significant potential for disease spread. Kenya camels have a massive capacity for rural and ASALs' livelihoods transformation but the identified health challenges, and other issues must be addressed. Further studies on the Kenyan camels' respiratory microbial ecology are important to understand microbial risks and reduce the burden of zoonotic infections. Intensification of risk communication and community engagement, and messaging targeted at behavior change interventions should be directed at camel value chain actors.

A shift from cattle to camel and goat farming can sustain milk production with lower inputs and emissions in north sub-Saharan Africa's drylands

Climate change is increasingly putting milk production from cattle-based dairy systems in north sub-Saharan Africa (NSSA) under stress, threatening livelihoods and food security. Here we combine livestock heat stress frequency, dry matter feed production and water accessibility data to understand where environmental changes in NSSA's drylands are jeopardizing cattle milk production. We show that environmental conditions worsened for ∼17% of the study area. Increasing goat and camel populations by ∼14% (∼7.7 million) and ∼10% (∼1.2 million), respectively, while reducing the dairy cattle population by ∼24% (∼5.9 million), could result in ∼0.14 Mt (+5.7%) higher milk production, lower water (-1,683.6 million m³, -15.3%) and feed resource (-404.3 Mt, -11.2%) demand-and lower dairy emissions by ∼1,224.6 MtCO₂e (-7.9%). Shifting herd composition from cattle towards the inclusion of, or replacement with, goats and camels can secure milk production and support NSSA's dairy production resilience against climate change.

Geospatial Analysis and Mapping Strategies for Fine-Grained and Detailed COVID-19 Data with GIS

The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects.

High MERS-CoV seropositivity associated with camel herd profile, husbandry practices and household socio-demographic characteristics in Northern Kenya

Despite high exposure to Middle East respiratory syndrome coronavirus (MERS-CoV), the predictors for seropositivity in the context of husbandry practices for camels in Eastern Africa are not well understood. We conducted a cross-sectional survey to describe the camel herd profile and determine the factors associated with MERS-CoV seropositivity in Northern Kenya. We enrolled 29 camel-owning households and administered questionnaires to collect herd and household data. Serum samples collected from 493 randomly selected camels were tested for anti-MERS-CoV antibodies using a microneutralisation assay, and regression analysis used to correlate herd and household characteristics with camel seropositivity. Households reared camels (median = 23 camels and IQR 16–56), and at least one other livestock species in two distinct herds; a home herd kept near homesteads, and a range/fora herd that resided far from the homestead. The overall MERS-CoV IgG seropositivity was 76.3%, with no statistically significant difference between home and fora herds. Significant predictors for seropositivity (P ⩽ 0.05) included camels 6–10 years old (aOR 2.3, 95% CI 1.0–5.2), herds with ⩾25 camels (aOR 2.0, 95% CI 1.2–3.4) and camels from Gabra community (aOR 2.3, 95% CI 1.2–4.2). These results suggest high levels of virus transmission among camels, with potential for human infection.

Middle East Respiratory Syndrome Coronavirus (MERS-CoV): State of the Science

Coronaviruses belong to a large family of viruses that can cause disease outbreaks ranging from the common cold to acute respiratory syndrome. Since 2003, three zoonotic members of this family evolved to cross species barriers infecting humans and resulting in relatively high case fatality rates (CFR). Compared to Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV, CFR = 10%) and pandemic Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2, CFR = 6%), the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) has scored the highest CFR (approximately 35%). In this review, we systematically summarize the current state of scientific knowledge about MERS-CoV, including virology and origin, epidemiology, zoonotic mode of transmission, and potential therapeutic or prophylactic intervention modalities.

Spatial association between primary Middle East respiratory syndrome coronavirus infection and exposure to dromedary camels in Saudi Arabia

Middle East respiratory syndrome coronavirus (MERS‐CoV) is an emerging zoonotic disease. Exposure to dromedary camels (Camelus dromedaries) has been consistently considered the main source of primary human infection. Although Saudi Arabia reports the highest rate of human MERS‐CoV infection and has one of the largest populations of dromedary camels worldwide, their spatial association has not yet been investigated. Thus, this study aimed to examine the correlation between the spatial distribution of primary MERS‐CoV cases with or without a history of camel exposure reported between 2012 and 2019 and dromedary camels at the provincial level in Saudi Arabia. In most provinces, a high proportion of older men develop infections after exposure to camels. Primary human infections during spring and winter were highest in provinces characterized by seasonal breeding and calving, increased camel mobilization and camel–human interactions. A strong and significant association was found between the total number of dromedary camels and the numbers of primary camel‐exposed and non‐exposed MERS‐CoV cases. Furthermore, spatial correlations between MERS‐CoV cases and camel sex, age and dairy status were significant. Via a cluster analysis, we identified Riyadh, Makkah and Eastern provinces as having the most primary MERS‐CoV cases and the highest number of camels. Transmission of MERS‐CoV from camels to humans occurs in most primary cases, but there is still a high proportion of primary infections with an ambiguous link to camels. The results from this study include significant correlations between primary MERS‐CoV cases and camel populations in all provinces, regardless of camel exposure history. This supports the hypothesis of the role of an asymptomatic human carrier or, less likely, an unknown animal host that has direct contact with both infected camels and humans. In this study, we performed a preliminary risk assessment of prioritization measures to control the transmission of infection from camels to humans.

Review of Geospatial Technology for Infectious Disease Surveillance: Use Case on COVID-19

This paper discusses on the increasing relevancy of geospatial technologies such as geographic information system (GIS) in the public health domain, particularly for the infectious disease surveillance and modelling strategies. Traditionally, the disease mapping tasks have faced many challenges—(1) authors rarely documented the evidence that were used to create map, (2) before evolution of GIS, many errors aroused in mapping tasks which were expanded extremely at global scales, and (3) there were no fidelity assessment of maps which resulted in inaccurate precision. This study on infectious diseases geo-surveillance is divided into four broad sections with emphasis on handling geographical and temporal issues to help in public health decision-making and planning policies: (1) geospatial mapping of diseases using its spatial and temporal information to understand their behaviour across geography; (2) the citizen’s involvement as volunteers in giving health and disease data to assess the critical situation for disease’s spread and prevention in neighbourhood effect; (3) scientific analysis of health-related behaviour using mathematical epidemiological and geo-statistical approaches with (4) capacity building program. To illustrate each theme, recent case studies are cited and case studies are performed on COVID-19 to demonstrate selected models.

A novel luciferase immunosorbent assay performs better than a commercial enzyme-linked immunosorbent assay to detect MERS-CoV specific IgG in humans and animals

The Middle East respiratory syndrome (MERS) is a lethal zoonosis caused by MERS coronavirus (MERS-CoV) and poses a significant threat to public health worldwide. Therefore, a rapid, sensitive, and specific serologic test for detecting anti-MERS-CoV antibodies in both humans and animals is urgently needed for the successful management of this illness. Here, we evaluated various novel luciferase immunosorbent assays (LISA) based on nucleocapsid protein (NP) as well as fragments derived from spike protein (S) including subunit 1 (S1), N terminal domain (NTD), receptor-binding domain (RBD) and subunit 2 (S2) of S for the detection of MERS-CoV-specific IgG. Fusion proteins, including nanoluciferase (NLuc) and various fragments derived from the NP or S protein of MERS-CoV, were expressed in human embryonic kidney 293 T cells. LISAs that detected anti-MERS-CoV IgG were further developed using cell lysates expressing various fusion proteins. Panels of human or animal samples infected with MERS-CoV were used to analyze the sensitivity and specificity of various LISAs in reference to a MERS-CoV RT-PCR, commercial S1-based ELISA, and pseudovirus particle neutralization test (ppNT). Our results showed that the S1-, RBD-, and NP-LISAs were more sensitive than the NTD- and S2-LISAs for the detection of anti-MERS-CoV IgG. Furthermore, the S1-, RBD-, and NP-LISAs were more sensitive (by at least 16-fold) than the commercially available S1-ELISA. Moreover, the S1-, RBD-, and NP-LISA specifically recognized anti-MERS-CoV IgG and did not cross-react with samples derived from other human CoV (OC43, 229E, HKU1, NL63)-infected patients. More importantly, these LISAs proved their applicability and reliability for detecting anti-MERS-CoV IgG in samples from camels, monkeys, and mice, among which the RBD-LISA exhibited excellent performance. The results of this study suggest that the novel MERS-CoV RBD- and S1- LISAs are highly effective platforms for the rapid and sensitive detection of anti-MERS-CoV IgG in human and animal samples. These assays have the potential to be used as serologic tests for the management and control of MERS-CoV infection.

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Scientific question

This study evaluated novel luciferase immunosorbent assays (LISAs) based on nucleocapsid protein (NP) as well as fragments derived from spike protein (S) for detection of MERS-CoV-specific IgG in humans and animals.

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Evidence before this study

Enzyme-linked immunosorbent assay (ELISA), microneutralization (MN), immunofluorescence assay (IFA), and pseudovirus particle neutralization test (ppNT) have been performed to detect serum antibodies against MERS-CoV. There remains a need to develop novel serological assays independent of protein purification, special secondary antibody, virus cultivation and Biosafety Level 3 (BSL-3) laboratory.

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New findings

In this study, novel LISAs based on the MERS-CoV S fragments and NP were developed. Human and animal samples infected with MERS-CoV were measured by the newly developed LISAs as well as reference methods including commercial S1-ELISA and ppNT. The results showed that the S1-, RBD-, and NP-LISAs were able to specifically distinguish MERS-CoV-infected samples from samples infected by other HCoV as consistent as the reference methods. Comparing with the commercially available S1-ELISA, the S1- and RBD-LISAs were 64-folds more sensitive. Moreover, the applicability and reliability of the LISAs were verified by detecting anti-MERS-CoV IgG in samples from camels, monkeys, and mice. The RBD-LISA exhibited superior sensitivity and specificity.

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Significance of the study

The novel MERS-CoV RBD- and S1-LISAs were developed independent of protein purification and special secondary antibody, and showed super specificity and efficiency for the detection of anti-MERS-CoV IgG in human and animal samples. These assays are recommended for serological diagnosis of MERS-CoV infection in the investigation of epidemic characteristic, origin tracing and vaccine study of MERS-CoV, they would contribute to the scientific control and prevention of MERS.

Force of infection of Middle East respiratory syndrome in dromedary camels in Kenya

Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic disease transmitted from dromedary camels to people, which can result in outbreaks with human-to-human transmission. Because it is a subclinical infection in camels, epidemiological measures other than prevalence are challenging to assess. This study estimated the force of infection (FOI) of MERS-CoV in camel populations from age-stratified serological data. A cross-sectional study of MERS-CoV was conducted in Kenya from July 2016 to July 2017. Seroprevalence was stratified into four age groups: <1, 1–2, 2–3 and >3 years old. Age-independent and age-dependent linear and quadratic generalised linear models were used to estimate FOI in pastoral and ranching camel herds. Models were compared based on computed AIC values. Among pastoral herds, the age-dependent quadratic FOI was the best fit model, while the age-independent FOI was the best fit for the ranching herd data. FOI provides an indirect estimate of infection risk, which is especially valuable where direct estimates of incidence and other measures of infection are challenging to obtain. The FOIs estimated in this study provide important insight about MERS-CoV dynamics in the reservoir species, and contribute to our understanding of the zoonotic risks of this important public health threat.

Spatiotemporal Clustering of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Incidence in Saudi Arabia, 2012-2019

Middle East respiratory syndrome coronavirus (MERS-CoV) is a great public health concern globally. Although 83% of the globally confirmed cases have emerged in Saudi Arabia, the spatiotemporal clustering of MERS-CoV incidence has not been investigated. This study analysed the spatiotemporal patterns and clusters of laboratory-confirmed MERS-CoV cases reported in Saudi Arabia between June 2012 and March 2019. Temporal, seasonal, spatial and spatiotemporal cluster analyses were performed using Kulldorff’s spatial scan statistics to determine the time period and geographical areas with the highest MERS-CoV infection risk. A strongly significant temporal cluster for MERS-CoV infection risk was identified between April 5 and May 24, 2014. Most MERS-CoV infections occurred during the spring season (41.88%), with April and May showing significant seasonal clusters. Wadi Addawasir showed a high-risk spatial cluster for MERS-CoV infection. The most likely high-risk MERS-CoV annual spatiotemporal clusters were identified for a group of cities (n = 10) in Riyadh province between 2014 and 2016. A monthly spatiotemporal cluster included Jeddah, Makkah and Taif cities, with the most likely high-risk MERS-CoV infection cluster occurring between April and May 2014. Significant spatiotemporal clusters of MERS-CoV incidence were identified in Saudi Arabia. The findings are relevant to control the spread of the disease. This study provides preliminary risk assessments for the further investigation of the environmental risk factors associated with MERS-CoV clusters.

Third Tofo Advanced Study Week on Emerging and Re-emerging Viruses, 2018

The Third Tofo Advanced Study Week on Emerging and Re-Emerging Viruses (3rd TASW) was held in Praia do Tofo, Mozambique, from September 02 to 06, 2018. It brought together 55 participants from 10 African countries as well as from Belgium, China, Germany, Singapore, and the USA. Meeting sessions covered aspects of the epidemiology, diagnosis, molecular and structural biology, vaccine development, and antiviral drug discovery for emerging RNA viruses that are current threats in Africa and included flaviviruses (dengue and Zika), alphaviruses (chikungunya), coronaviruses, filoviruses (Ebola), influenza viruses, Crimean Congo hemorrhagic fever virus, Rift Valley fever Virus, Lassa virus, and others. Data were presented on recent flavivirus and/or chikungunyavirus outbreaks in Angola, Burkina Faso, and Mozambique. In addition, these viruses are endemic in many sub-Saharan countries. The TASW series on emerging viruses is unique in Africa and successful in promoting collaborations between researchers in Africa and other parts of the world, as well as among African scientists. This report summarizes the lectures held at the meeting and highlights advances in the field.

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The 3rd Tofo Advanced Study Week on Emerging and Re-emerging Viruses took place from September 2–6, 2018.

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African attendees came from Angola, Botswana, Burkina Faso, the CAR, Mozambique, Nigeria, S Africa, Tanzania and Zimbabwe.

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Other participants were from Europe, China, Singapore, and the USA.

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This unique meeting enabled scientists from Africa and elsewhere to discuss problems and initiate new collaborations.

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Presentations covered dengue virus, Zika, chikungunya, coronaviruses, Ebola, influenza, Rift Valley fever, CCHF, and RSV.