Estimating the Impact of Vaccination Campaigns on Measles Transmission in Somalia.

Somalia is a complex and fragile setting with a demonstrated potential for disruptive, high-burden measles outbreaks. In response, since 2018, Somalian authorities have partnered with UNICEF and the WHO to implement measles vaccination campaigns across the country. In this paper, we create a Somalia-specific model of measles transmission based on a comprehensive epidemiological dataset including case-based surveillance, vaccine registries, and serological surveys. We use this model to assess the impact of these campaign interventions on Somalian's measles susceptibility, showing, for example, that across the roughly 10 million doses delivered, 1 of every 5 immunized a susceptible child. Finally, we use the model to explore a counter-factual epidemiology without the 2019-2020 campaigns, and we estimate that those interventions prevented over 10,000 deaths.

Characterization of COVID-19 cases in the early phase (March to July 2020) of the pandemic in Kenya.

Background: Kenya detected the first case of COVID-19 on March 13, 2020, and as of July 30, 2020, 17 975 cases with 285 deaths (case fatality rate (CFR) = 1.6%) had been reported. This study described the cases during the early phase of the pandemic to provide information for monitoring and response planning in the local context. Methods: We reviewed COVID-19 case records from isolation centres while considering national representation and the WHO sampling guideline for clinical characterization of the COVID-19 pandemic within a country. Socio-demographic, clinical, and exposure data were summarized using median and mean for continuous variables and proportions for categorical variables. We assigned exposure variables to socio-demographics, exposure, and contact data, while the clinical spectrum was assigned outcome variables and their associations were assessed. Results: A total of 2796 case records were reviewed including 2049 (73.3%) male, 852 (30.5%) aged 30-39 years, 2730 (97.6%) Kenyans, 636 (22.7%) transporters, and 743 (26.6%) residents of Nairobi City County. Up to 609 (21.8%) cases had underlying medical conditions, including hypertension (n = 285 (46.8%)), diabetes (n = 211 (34.6%)), and multiple conditions (n = 129 (21.2%)). Out of 1893 (67.7%) cases with likely sources of exposure, 601 (31.8%) were due to international travel. There were 2340 contacts listed for 577 (20.6%) cases, with 632 contacts (27.0%) being traced. The odds of developing COVID-19 symptoms were higher among case who were aged above 60 years (odds ratio (OR) = 1.99, P = 0.007) or had underlying conditions (OR = 2.73, P < 0.001) and lower among transport sector employees (OR = 0.31, P < 0.001). The odds of developing severe COVID-19 disease were higher among cases who had underlying medical conditions (OR = 1.56, P < 0.001) and lower among cases exposed through community gatherings (OR = 0.27, P < 0.001). The odds of survival of cases from COVID-19 disease were higher among transport sector employees (OR = 3.35, P = 0.004); but lower among cases who were aged ≥60 years (OR = 0.58, P = 0.034) and those with underlying conditions (OR = 0.58, P = 0.025). Conclusion: The early phase of the COVID-19 pandemic demonstrated a need to target the elderly and comorbid cases with prevention and control strategies while closely monitoring asymptomatic cases.

Transcriptome analysis of Rafflesia cantleyi flower stages reveals insights into the regulation of senescence.

Rafflesia is a unique plant species existing as a single flower and produces the largest flower in the world. While Rafflesia buds take up to 21 months to develop, its flowers bloom and wither within about a week. In this study, transcriptome analysis was carried out to shed light on the molecular mechanism of senescence in Rafflesia. A total of 53.3 million high quality reads were obtained from two Rafflesia cantleyi flower developmental stages and assembled to generate 64,152 unigenes. Analysis of this dataset showed that 5,166 unigenes were differentially expressed, in which 1,073 unigenes were identified as genes involved in flower senescence. Results revealed that as the flowers progress to senescence, more genes related to flower senescence were significantly over-represented compared to those related to plant growth and development. Senescence of the R. cantleyi flower activates senescence-associated genes in the transcription activity (members of the transcription factor families MYB, bHLH, NAC, and WRKY), nutrient remobilization (autophagy-related protein and transporter genes), and redox regulation (CATALASE). Most of the senescence-related genes were found to be differentially regulated, perhaps for the fine-tuning of various responses in the senescing R. cantleyi flower. Additionally, pathway analysis showed the activation of genes such as ETHYLENE RECEPTOR, ETHYLENE-INSENSITIVE 2, ETHYLENE-INSENSITIVE 3, and ETHYLENE-RESPONSIVE TRANSCRIPTION FACTOR, indicating the possible involvement of the ethylene hormone response pathway in the regulation of R. cantleyi senescence. Our results provide a model of the molecular mechanism underlying R. cantleyi flower senescence, and contribute essential information towards further understanding the biology of the Rafflesiaceae family.

Transcriptome landscape of Rafflesia cantleyi floral buds reveals insights into the roles of transcription factors and phytohormones in flower development.

Rafflesia possesses unique biological features and known primarily for producing the world's largest and existing as a single flower. However, to date, little is known about key regulators participating in Rafflesia flower development. In order to further understand the molecular mechanism that regulates Rafflesia cantleyi flower development, RNA-seq data from three developmental stages of floral bud, representing the floral organ primordia initiation, floral organ differentiation, and floral bud outgrowth, were analysed. A total of 89,890 transcripts were assembled of which up to 35% could be annotated based on homology search. Advanced transcriptome analysis using K-mean clustering on the differentially expressed genes (DEGs) was able to identify 12 expression clusters that reflect major trends and key transitional states, which correlate to specific developmental stages. Through this, comparative gene expression analysis of different floral bud stages identified various transcription factors related to flower development. The members of WRKY, NAC, bHLH, and MYB families are the most represented among the DEGs, suggesting their important function in flower development. Furthermore, pathway enrichment analysis also revealed DEGs that are involved in various phytohormone signal transduction events such as auxin and auxin transport, cytokinin and gibberellin biosynthesis. Results of this study imply that transcription factors and phytohormone signalling pathways play major role in Rafflesia floral bud development. This study provides an invaluable resource for molecular studies of the flower development process in Rafflesia and other plant species.

Perigone Lobe Transcriptome Analysis Provides Insights into Rafflesia cantleyi Flower Development.

Rafflesia is a biologically enigmatic species that is very rare in occurrence and possesses an extraordinary morphology. This parasitic plant produces a gigantic flower up to one metre in diameter with no leaves, stem or roots. However, little is known about the floral biology of this species especially at the molecular level. In an effort to address this issue, we have generated and characterised the transcriptome of the Rafflesia cantleyi flower, and performed a comparison with the transcriptome of its floral bud to predict genes that are expressed and regulated during flower development. Approximately 40 million sequencing reads were generated and assembled de novo into 18,053 transcripts with an average length of 641 bp. Of these, more than 79% of the transcripts had significant matches to annotated sequences in the public protein database. A total of 11,756 and 7,891 transcripts were assigned to Gene Ontology categories and clusters of orthologous groups respectively. In addition, 6,019 transcripts could be mapped to 129 pathways in Kyoto Encyclopaedia of Genes and Genomes Pathway database. Digital abundance analysis identified 52 transcripts with very high expression in the flower transcriptome of R. cantleyi. Subsequently, analysis of differential expression between developing flower and the floral bud revealed a set of 105 transcripts with potential role in flower development. Our work presents a deep transcriptome resource analysis for the developing flower of R. cantleyi. Genes potentially involved in the growth and development of the R. cantleyi flower were identified and provide insights into biological processes that occur during flower development.

Reducing routine vaccination dropout rates: evaluating two interventions in three Kenyan districts, 2014.

BACKGROUND: Globally, vaccine preventable diseases are responsible for nearly 20% of deaths annually among children <5 years old. Worldwide, many children dropout from the vaccination program, are vaccinated late, or incompletely vaccinated. We evaluated the impact of text messaging and sticker reminders to reduce dropouts from the vaccination program. METHODS: The evaluation was conducted in three selected districts in Kenya: Machakos, Langata and Njoro. Three health facilities were selected in each district, and randomly allocated to send text messages or provide stickers reminding parents to bring their children for second and third dose of pentavalent vaccine, or to the control group (routine reminder) with next appointment date indicated on the well-child booklet. Children aged <12 months presenting for their first dose of pentavalent vaccine were enrolled. A dropout was defined as not returning for vaccination ≥ 2 weeks after scheduled date for third dose of pentavalent vaccine. We calculated dropout rate as a percentage of the difference between first and third pentavalent dose. RESULTS: We enrolled 1,116 children; 372 in each intervention and 372 controls between February and October 2014. Median age was 45 days old (range: 31-99 days), and 574 (51%) were male. There were 136 (12%) dropouts. Thirteen (4%) children dropped out among those who received text messages, 60 (16%) among who received sticker reminders, and 63 (17%) among the controls. Having a caregiver with below secondary education [Odds Ratio (OR) 1.8, 95% Confidence Interval (CI) 1.1-3.2], and residing >5 km from health facility (OR 1.6, CI 1.0-2.7) were associated with higher odds of dropping out. Those who received text messages were less likely to drop out compared to controls (OR 0.2, CI 0.04-0.8). There was no statistical difference between those who received stickers and controls (OR 0.9, CI 0.5-1.6). CONCLUSION: Text message reminders can reduce vaccination dropout rates in Kenya. We recommend the extended implementation of text message reminders in routine vaccination services.