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BACKGROUND Amidst the COVID-19 pandemic, there has been a need for rapid social understanding to inform infodemic management and response. While social media analysis platforms have traditionally been designed for commercial brands for marketing and sales purposes, it has been under-utilized and under-adapted for comprehensive understanding of social dynamics in areas such as public health. Traditional systems have challenges for public health usage and new tools and innovative methods are needed. The WHO Early AI-Supported Response with Social Listening (EARS) platform was developed to overcome some of these challenges. OBJECTIVE To describe the methodological approach to the development of the EARS platform, including data sourcing, development and validation of a machine learning categorization approach, as well as results from the pilot. METHODS Data for EARS is collected daily from online conversations in publicly available sources, including Twitter, Facebook public pages, online forums, news comments, and blogs in 9 languages. Public health and social media experts developed a taxonomy to categorize COVID-19 narratives to 5 relevant main categories and 41 sub-categories. We developed a semi-supervised machine learning algorithm to categorize social media posts to categories and various filters. To validate the results obtained by the machine learning-based approach we compared it to a search filters methodology applying boolean queries with the same amount of information and measured recall and precision. A Hotelling T2 was run to determine the effect of the classification method on the combined variables. RESULTS The EARS platform has been developed, validated and applied to monitor the conversation about COVID-19 since December 2020. A total of 215,469,045 social posts were collected for processing from December 2020 to February 2022. The machine learning algorithm outperformed the boolean search filters method by a large margin for precision and recall in both English and Spanish (p CONCLUSIONS The EARS platform has been specifically developed to address the changing needs of public health analysts during the COVID-19 pandemic. The application of a public health taxonomy and AI technology to a user-friendly social listening platform, accessible directly by analysts, is a significant step in better enabling understanding of global narratives. The platform was designed in a way to allow for scalability, and iterations and new countries and languages have been added. This research has shown that a machine learning approach is more accurate than using only keywords and has benefit for categorizing and understanding large amounts of digital social data during an infodemic. Further technical developments are needed and planned to provide continuous improvements and meet the challenges in generation of infodemic insights from social media faced by infodemic managers and public health professionals.

Background Contact tracing is one of the key interventions in response to the COVID-19 pandemic but its implementation varies widely across countries. There is little guidance on how to monitor contact tracing performance, and no systematic overview of indicators to assess contact tracing systems or conceptual framework for such indicators exists to date. Methods We conducted a rapid scoping review using a systematic literature search strategy in the peer-reviewed and grey literature as well as open source online documents. We developed a conceptual framework to map indicators by type (input, process, output, outcome, impact) and thematic area (human resources, financial resources, case investigation, contact identification, contact testing, contact follow up, case isolation, contact quarantine, transmission chain interruption, incidence reduction). Results We identified a total of 153 contact tracing indicators from 1,555 peer-reviewed studies, 894 studies from grey literature sources, and 15 sources from internet searches. Two-thirds of indicators were process indicators (102; 67%), while 48 (31%) indicators were output indicators. Only three (2%) indicators were input indicators. Indicators covered seven out of ten conceptualized thematic areas, with more than half being related to either case investigation (37; 24%) or contact identification (44; 29%). There were no indicators for the input area “financial resources”, the outcome area “transmission chain interruption”, and the impact area “incidence reduction”. Conclusions Almost all identified indicators were either process or output indicators focusing on case investigation, contact identification, case isolation or contact quarantine. We identified important gaps in input, outcome and impact indicators, which constrains evidence-based assessment of contact tracing systems. A universally agreed set of indicators is needed to allow for cross-system comparisons and to improve the performance of contact tracing systems.

Norovirus (NoV) in ready to eat food has recently been defined as one of the virus-food commodity combinations with greatest public health concern. The role of food handlers therein has well been recognized. The aim of this study was to identify gaps in food handlers' education and to investigate possible associations between reported behavior, knowledge and awareness of NoV, and environmental presence of NoV. For this, face-to-face interviews were conducted using structured questionnaires in 1023 catering companies (i.e. restaurants mainly), 101 non-hospital health care centers, 52 hospital central kitchens and in 102 hospital in-patient units. In addition, three surface swabs were taken at each setting. Multivariate logistic regression was performed on data restricted to NoV high season months only, in which NoV was present in 21/374 (6%) catering companies and 37/233 (16%) institutional settings (p

Item does not contain fulltext During September and October 2010, the Dutch Public Health Institute detected an enterovirus (EV) 68 (EV68) epidemic in the Netherlands through general practitioner-based surveillance of acute respiratory infections. EV68 shares phenotypic and genotypic properties with human rhinovirus (HRV). Despite increased EV and HRV detections, Dutch clinical laboratories did not identify EV68. To assess the capability of Dutch clinical laboratories to detect EV68, ten laboratories with more than eight detected EV and HRV cases in September and October 2010 provided information about their detection algorithms and testing results for a 2010 Dutch EV68 strain. For EV detection mostly stool specimens (median 49%), respiratory specimens (median 27%) and cerebrospinal fluid (median 22%) were used. For HRV detection only respiratory specimens were used. Except for the Seeplex(R) RV15ACE EV-specific assay, all EV and 73% of HRV assays, including those of the Public Health Institute, were able to detect EV68. Two-step EV RT-PCR protocols were the most sensitive. Thus, laboratories might have misidentified EV68 as HRV. In addition, EV68 cases might have also been missed because patients with respiratory diseases are usually not tested for EV infection. Therefore, clinical laboratories should include EV detection in the differential diagnosis of patients presenting with respiratory symptoms. 01 juni 2013

Between December 2013 and April 2016, the largest epidemic of Ebola virus disease (EVD) to date generated more than 28,000 cases and more than 11,000 deaths in the large, mobile populations of Guinea, Liberia, and Sierra Leone. Tracking the rapid rise and slower decline of the West African epidemic has reinforced some common understandings about the epidemiology and control of EVD but has also generated new insights. Despite having more information about the geographic distribution of the disease, the risk of human infection from animals and from survivors of EVD remains unpredictable over a wide area of equatorial Africa. Until human exposure to infection can be anticipated or avoided, future outbreaks will have to be managed with the classic approach to EVD control — extensive surveillance, rapid detection and diagnosis, comprehensive tracing of contacts, prompt patient isolation, supportive clinical care, rigorous efforts to prevent and control infection, safe and dignified burial, and engagement of the community. Empirical and modeling studies conducted during the West African epidemic have shown that large epidemics of EVD are preventable — a rapid response can interrupt transmission and restrict the size of outbreaks, even in densely populated cities. The critical question now is how to ensure that populations and their health services are ready for the next outbreak, wherever it may occur. Health security across Africa and beyond depends on committing resources to both strengthen national health systems and sustain investment in the next generation of vaccines, drugs, and diagnostics.

Following an increase in detection of enterovirus 68 (EV68) in community surveillance of respiratory infections in The Netherlands in 2010, epidemiological and virological analyses were performed to investigate the possible public health impact of EV68 infections. We retrospectively tested specimens collected from acute respiratory infections surveillance and through three children cohort studies conducted in The Netherlands from 1994 through 2010. A total of 71 of 13,310 (0.5%) specimens were positive for EV68, of which 67 (94%) were from symptomatic persons. Twenty-four (34%) of the EV68 positive specimens were collected during 2010. EV68-positive patients with respiratory symptoms showed significantly more dyspnea, cough and bronchitis than EV68-negative patients with respiratory symptoms. Phylogenetic analysis showed an increased VP1 gene diversity in 2010, suggesting that the increased number of EV68 detections in 2010 reflects a real epidemic. Clinical laboratories should consider enterovirus diagnostics in the differential diagnosis of patients presenting with respiratory symptoms. (C) 2011 Elsevier Inc. All rights reserved.

A nanopore DNA sequencer is used for real-time genomic surveillance of the Ebola virus epidemic in the field in Guinea; the authors demonstrate that it is possible to pack a genomic surveillance laboratory in a suitcase and transport it to the field for on-site virus sequencing, generating results within 24 hours of sample collection. This paper reports the use of nanopore DNA sequencers (known as MinIONs) for real-time genomic surveillance of the Ebola virus epidemic, in the field in Guinea. The authors demonstrate that it is possible to pack a genomic surveillance laboratory in a suitcase and transport it to the field for on-site virus sequencing, generating results within 24 hours of sample collection. The Ebola virus disease epidemic in West Africa is the largest on record, responsible for over 28,599 cases and more than 11,299 deaths1. Genome sequencing in viral outbreaks is desirable to characterize the infectious agent and determine its evolutionary rate. Genome sequencing also allows the identification of signatures of host adaptation, identification and monitoring of diagnostic targets, and characterization of responses to vaccines and treatments. The Ebola virus (EBOV) genome substitution rate in the Makona strain has been estimated at between 0.87 × 10−3 and 1.42 × 10−3 mutations per site per year. This is equivalent to 16–27 mutations in each genome, meaning that sequences diverge rapidly enough to identify distinct sub-lineages during a prolonged epidemic2,3,4,5,6,7. Genome sequencing provides a high-resolution view of pathogen evolution and is increasingly sought after for outbreak surveillance. Sequence data may be used to guide control measures, but only if the results are generated quickly enough to inform interventions8. Genomic surveillance during the epidemic has been sporadic owing to a lack of local sequencing capacity coupled with practical difficulties transporting samples to remote sequencing facilities9. To address this problem, here we devise a genomic surveillance system that utilizes a novel nanopore DNA sequencing instrument. In April 2015 this system was transported in standard airline luggage to Guinea and used for real-time genomic surveillance of the ongoing epidemic. We present sequence data and analysis of 142 EBOV samples collected during the period March to October 2015. We were able to generate results less than 24 h after receiving an Ebola-positive sample, with the sequencing process taking as little as 15–60 min. We show that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.

Q fever is a notifiable disease in the Netherlands: laboratories are obliged to notify possible cases to the Municipal Health Services. These services then try to reconfirm cases with additional clinical and epidemiological data and provide anonymised reports to the national case register of notifiable diseases. Since the start of the 2007-2009 Dutch Q fever outbreak, notification rules remained unchanged, despite new laboratory insights and altered epidemiology. In this study, we retrospectively analysed how these changes influenced the proportion of laboratory-defined acute Q fever cases (confirmed, probable and possible) that were included in the national case register, during (2009) and after the outbreak (2010 and 2011). The number of laboratory-defined cases notified to the Municipal Health Services was 377 in2009, 96 in 2010 and 50 in 2011. Of these, 186 (49.3%) in 2009, 12 (12.5%) in 2010 and 9 (18.0%) in 2011 were confirmed as acute infection by laboratory interpretation. The proportion of laboratory-defined acute Q fever cases that was reconfirmed by the Municipal Health Services and that were included in the national case register decreased from 90% in 2009, to 22% and 24% in 2010 and 2011, respectively. The decrease was observed in all categories of cases, including those considered to be confirmed by laboratory criteria. Continued use of a pre-outbreak case definition led to over-reporting of cases to the Municipal Health Services in the post-epidemic years. Therefore we recommend dynamic laboratory notification rules, by reviewing case definitions periodically in an ongoing epidemic, as in the Dutch Q fever outbreak. .

Plasmodium falciparum lines differ in their ability to infect mosquitoes. The Anopheles gambiae L3-5 refractory (R) line melanizes most Plasmodium species, including the Brazilian P. falciparum 7G8 line, but it is highly susceptible to some African P. falciparum strains such as 3D7, NF54, and GB4. We investigated whether these lines differ in their ability to evade the mosquito immune system. Silencing key components of the mosquito complement-like system [thioester-containing protein 1 (TEP1), leucine-rich repeat protein 1, and Anopheles Plasmodium -responsive leucine-rich repeat protein 1] prevented melanization of 7G8 parasites, reverting the refractory phenotype. In contrast, it had no effect on the intensity of infection with NF54, suggesting that this line is able to evade TEP1-mediated lysis. When R females were coinfected with a line that is melanized (7G8) and a line that survives (3D7), the coinfection resulted in mixed infections with both live and encapsulated parasites on individual midguts. This finding shows that survival of individual parasites is parasite-specific and not systemic in nature, because parasites can evade TEP1-mediated lysis even when other parasites are melanized in the same midgut. When females from an extensive genetic cross between R and susceptible A. gambiae (G3) mosquitoes were infected with P. berghei , encapsulation was strongly correlated with the TEP1-R1 allele. However, P. falciparum 7G8 parasites were no longer encapsulated by females from this cross, indicating that the TEP1-R1 allele is not sufficient to melanize this line. Evasion of the A. gambiae immune system by P. falciparum may be the result of parasite adaptation to sympatric mosquito vectors and may be an important factor driving malaria transmission.

Objective— The coagulation-inflammation cycle has been implicated as a critical component in malaria pathogenesis. Defibrotide (DF), a mixture of DNA aptamers, displays anticoagulant, anti-inflammatory, and endothelial cell (EC)-protective activities and has been successfully used to treat comatose children with veno-occlusive disease. DF was investigated here as a drug to treat cerebral malaria. Methods and Results— DF blocks tissue factor expression by ECs incubated with parasitized red blood cells and attenuates prothrombinase activity, platelet aggregation, and complement activation. In contrast, it does not affect nitric oxide bioavailability. We also demonstrated that Plasmodium falciparum glycosylphosphatidylinositol ( Pf -GPI) induces tissue factor expression in ECs and cytokine production by dendritic cells. Notably, dendritic cells, known to modulate coagulation and inflammation systemically, were identified as a novel target for DF. Accordingly, DF inhibits Toll-like receptor ligand-dependent dendritic cells activation by a mechanism that is blocked by adenosine receptor antagonist (8-p-sulfophenyltheophylline) but not reproduced by synthetic poly-A, -C, -T, and -G. These results imply that aptameric sequences and adenosine receptor mediate dendritic cells responses to the drug. DF also prevents rosetting formation, red blood cells invasion by P. falciparum and abolishes oocysts development in Anopheles gambiae. In a murine model of cerebral malaria, DF affected parasitemia, decreased IFN-γ levels, and ameliorated clinical score (day 5) with a trend for increased survival. Conclusion— Therapeutic use of DF in malaria is proposed.

Phlebotomus duboscqi is the principle vector of Leishmania major, the causative agent of cutaneous leishmaniasis (CL), in West Africa and is the suspected vector in Mali. Although found throughout the country the seasonality and infection prevalence of P. duboscqi has not been established in Mali. We conducted a three year study in two neighboring villages, Kemena and Sougoula, in Central Mali, an area with a leishmanin skin test positivity of up to 45%. During the first year, we evaluated the overall diversity of sand flies. Of 18,595 flies collected, 12,952 (69%) belonged to 12 species of Sergentomyia and 5,643 (31%) to two species of the genus Phlebotomus, P. duboscqi and P. rodhaini. Of those, P. duboscqi was the most abundant, representing 99% of the collected Phlebotomus species. P. duboscqi was the primary sand fly collected inside dwellings, mostly by resting site collection. The seasonality and infection prevalence of P. duboscqi was monitored over two consecutive years. P. dubsocqi were collected throughout the year. Using a quasi-Poisson model we observed a significant annual (year 1 to year 2), seasonal (monthly) and village effect (Kemena versus Sougoula) on the number of collected P. duboscqi. The significant seasonal effect of the quasi-Poisson model reflects two seasonal collection peaks in May-July and October-November. The infection status of pooled P. duboscqi females was determined by PCR. The infection prevalence of pooled females, estimated using the maximum likelihood estimate of prevalence, was 2.7% in Kemena and Sougoula. Based on the PCR product size, L. major was identified as the only species found in flies from the two villages. This was confirmed by sequence alignment of a subset of PCR products from infected flies to known Leishmania species, incriminating P. duboscqi as the vector of CL in Mali., Author Summary Female sand flies transmit a parasite called Leishmania that causes a disease called cutaneous leishmaniasis (CL). Several species of sand flies are found in West Africa, but only one species, Phlebotomus duboscqi, has been proven to transmit the parasite. Cutaneous Leishmaniasis has also been reported from Mali, Central West Africa, but the sand fly transmitting the parasite and its annual abundance has not been established, until now. Sand flies were collected during three consecutive years from two neighboring villages in Central Mali, Kemena and Sougoula, where CL is present. P. duboscqi was collected year-round and was the dominant sand fly inside of and surrounding human dwellings. Other sand fly species, known not to be vectors of CL, were primarily found outside the village. Additionally, P. duboscqi females were found infected with L. major, the same Leishmania species identified from human CL cases in Mali. The estimated infection prevalence of P. duboscqi females was 2.7%. Interestingly, the sand fly abundance and infection prevalence was similar in the two villages despite a previous report indicating a disparate L. major exposure rate in humans. This study greatly enhances our knowledge of CL transmission in Mali, poorly studied in this country to date.

We performed a forward genetic screen, using Drosophila as a surrogate mosquito, to identify host factors required for the growth of the avian malaria parasite, Plasmodium gallinaceum. We identified 18 presumed loss-of-function mutants that reduced the growth of the parasite in flies. Presumptive mutation sites were identified in 14 of the mutants on the basis of the insertion site of a transposable element. None of the identified genes have been previously implicated in innate immune responses or interactions with Plasmodium. The functions of five Anopheles gambiae homologs were tested by using RNAi to knock down gene function followed by measuring the growth of the rodent parasite, Plasmodium berghei. Loss of function of four of these genes in the mosquito affected Plasmodium growth, suggesting that Drosophila can be used effectively as a surrogate mosquito to identify relevant host factors in the mosquito.

The involvement of reactive oxygen species (ROS) in mosquito immunity against bacteria and Plasmodium was investigated in the malaria vector Anopheles gambiae. Strains of An. gambiae with higher systemic levels of ROS survive a bacterial challenge better, whereas reduction of ROS by dietary administration of antioxidants significantly decreases survival, indicating that ROS are required to mount effective antibacterial responses. Expression of several ROS detoxification enzymes increases in the midgut and fat body after a blood meal. Furthermore, expression of several of these enzymes increases to even higher levels when mosquitoes are fed a Plasmodium berghei-infected meal, indicating that the oxidative stress after a blood meal is exacerbated by Plasmodium infection. Paradoxically, a complete lack of induction of catalase mRNA and lower catalase activity were observed in P. berghei-infected midguts. This suppression of midgut catalase expression is a specific response to ookinete midgut invasion and is expected to lead to higher local levels of hydrogen peroxide. Further reduction of catalase expression by double-stranded RNA-mediated gene silencing promoted parasite clearance by a lytic mechanism and reduced infection significantly. High mosquito mortality is often observed after P. berghei infection. Death appears to result in part from excess production of ROS, as mortality can be decreased by oral administration of uric acid, a strong antioxidant. We conclude that ROS modulate An. gambiae immunity and that the mosquito response to P. berghei involves a local reduction of detoxification of hydrogen peroxide in the midgut that contributes to limit Plasmodium infection through a lytic mechanism.

This study analyzes data from 19 countries (from April 2009 to Jan 2010), comprising some 70,000 hospitalized patients with severe H1N1 infection, to reveal risk factors for severe pandemic influenza, which include chronic illness, cardiac disease, chronic respiratory disease, and diabetes., Background Since the start of the 2009 influenza A pandemic (H1N1pdm), the World Health Organization and its member states have gathered information to characterize the clinical severity of H1N1pdm infection and to assist policy makers to determine risk groups for targeted control measures. Methods and Findings Data were collected on approximately 70,000 laboratory-confirmed hospitalized H1N1pdm patients, 9,700 patients admitted to intensive care units (ICUs), and 2,500 deaths reported between 1 April 2009 and 1 January 2010 from 19 countries or administrative regions—Argentina, Australia, Canada, Chile, China, France, Germany, Hong Kong SAR, Japan, Madagascar, Mexico, the Netherlands, New Zealand, Singapore, South Africa, Spain, Thailand, the United States, and the United Kingdom—to characterize and compare the distribution of risk factors among H1N1pdm patients at three levels of severity: hospitalizations, ICU admissions, and deaths. The median age of patients increased with severity of disease. The highest per capita risk of hospitalization was among patients, Editors' Summary Background In April 2009, a new strain of influenza A H1N1 was first identified in Mexico and the United States and subsequently spread around the world. In June 2009, the World Health Organization (WHO) declared a pandemic alert phase 6, which continued until August 2010. Throughout the pandemic, WHO and member states gathered information to characterize the patterns of risk associated with the new influenza A H1N1 virus infection and to assess the clinical picture. Although risk factors for severe disease following seasonal influenza infection have been well documented in many countries (for example, pregnancy; chronic medical conditions such as pulmonary, cardiovascular, renal, hepatic, neuromuscular, hematologic, and metabolic disorders; some cognitive conditions; and immunodeficiency), risk factors for severe disease following infection early in the 2009 H1N1 pandemic were largely unknown. Why Was This Study Done? Many countries have recently reported data on the association between severe H1N1 influenza and a variety of underlying risk factors, but because these data are presented in different formats, making direct comparisons across countries is difficult, with no clear consensus for some conditions. Therefore, to assess the frequency and distribution of known and new potential risk factors for severe H1N1 infection, this study was conducted to collect data (from 1 April 2009 to 1 January 2010) from surveillance programs of the Ministries of Health or National Public Health Institutes in 19 countries―Argentina, Australia, Canada, Chile, China, France, Germany, Hong Kong (special administrative region), Japan, Madagascar, Mexico, the Netherlands, New Zealand, Singapore, South Africa, Spain, Thailand, the United States, and the United Kingdom. What Did the Researchers Do and Find? As part of routine surveillance, countries were asked to provide risk factor data on laboratory-confirmed H1N1 in patients who were admitted to hospital, admitted to the intensive care unit (ICU), or had died because of their infection, using a standardized format. The researchers grouped potential risk conditions into four categories: age, chronic medical illnesses, pregnancy (by trimester), and other conditions that were not previously considered as risk conditions for severe influenza outcomes, such as obesity. For each risk factor (except pregnancy), the researchers calculated the percentage of each group of patients using the total number of cases reported in each severity category (hospitalization, admission to ICU, and death). To evaluate the risk associated with pregnancy, the researchers used the ratio of pregnant women to all women of childbearing age (age 15–49 years) at each level of severity to describe the differences between levels. The researchers were able to collect data on approximately 70,000 patients requiring hospitalization, 9,700 patients admitted to the ICU, and 2,500 patients who died from H1N1 infection. The proportion of patients with H1N1 with one or more reported chronic conditions increased with severity—the median was 31.1% of hospitalized patients, 52.3% of patients admitted to the ICU, and 61.8% of patients who died. For all levels of severity, pregnant women in their third trimester consistently accounted for the majority of the total of pregnant women. The proportion of patients with obesity increased with increasing disease severity—median of 6% of hospitalized patients, 11.3% of patients admitted to the ICU, and 12.0% of all deaths from H1N1. What Do These Findings Mean? These findings show that risk factors for severe H1N1 infection are similar to those for seasonal influenza, with some notable differences: a substantial proportion of people with severe and fatal cases of H1N1 had pre-existing chronic illness, which indicates that the presence of chronic illness increases the likelihood of death. Cardiac disease, chronic respiratory disease, and diabetes are important risk factors for severe disease that will be especially relevant for countries with high rates of these illnesses. Approximately 2/3 of hospitalized people and 40% of people who died from H1N1 infection did not have any identified pre-existing chronic illness, but this study was not able to comprehensively assess how many of these cases had other risk factors, such as pregnancy, obesity, smoking, and alcohol misuse. Because of large differences between countries, the role of risk factors such as obesity and pregnancy need further study—although there is sufficient evidence to support vaccination and early intervention for pregnant women. Overall, the findings of this study reinforce the need to identify and target high-risk groups for interventions such as immunization, early medical advice, and use of antiviral medications. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001053. WHO provides a Global Alert and Response (GAR) with updates on a number of influenza-related topics The US Centers for Disease Control and Prevention provides information on risk factors and H1N1

Background OXR1 is an ancient gene, present in all eukaryotes examined so far that confers protection from oxidative stress by an unknown mechanism. The most highly conserved region of the gene is the carboxyl-terminal TLDc domain, which has been shown to be sufficient to prevent oxidative damage. Methodology/Principal Findings OXR1 has a complex genomic structure in the mosquito A. gambiae, and we confirm that multiple splice forms are expressed in adult females. Our studies revealed that OXR1 regulates the basal levels of catalase (CAT) and glutathione peroxidase (Gpx) expression, two enzymes involved in detoxification of hydrogen peroxide, giving new insight into the mechanism of action of OXR1. Gene silencing experiments indicate that the Jun Kinase (JNK) gene acts upstream of OXR1 and also regulates expression of CAT and GPx. Both OXR1 and JNK genes are required for adult female mosquitoes to survive chronic oxidative stress. OXR1 silencing decreases P. berghei oocyst formation. Unexpectedly, JNK silencing has the opposite effect and enhances Plasmodium infection in the mosquito, suggesting that JNK may also mediate some, yet to be defined, antiparasitic response. Conclusion The JNK pathway regulates OXR1 expression and OXR1, in turn, regulates expression of enzymes that detoxify reactive oxygen species (ROS) in Anopheles gambiae. OXR1 silencing decreases Plasmodium infection in the mosquito, while JNK silencing has the opposite effect and enhances infection.

Background Functional screens based on dsRNA-mediated gene silencing identified several Anopheles gambiae genes that limit Plasmodium berghei infection. However, some of the genes identified in these screens have no effect on the human malaria parasite Plasmodium falciparum; raising the question of whether different mosquito effector genes mediate anti-parasitic responses to different Plasmodium species. Results Four new An. gambiae (G3) genes were identified that, when silenced, have a different effect on P. berghei (Anka 2.34) and P. falciparum (3D7) infections. Orthologs of these genes, as well as LRIM1 and CTL4, were also silenced in An. stephensi (Nijmegen Sda500) females infected with P. yoelii (17XNL). For five of the six genes tested, silencing had the same effect on infection in the P. falciparum-An. gambiae and P. yoelii-An. stephensi parasite-vector combinations. Although silencing LRIM1 or CTL4 has no effect in An. stephensi females infected with P. yoelii, when An. gambiae is infected with the same parasite, silencing these genes has a dramatic effect. In An. gambiae (G3), TEP1, LRIM1 or LRIM2 silencing reverts lysis and melanization of P. yoelii, while CTL4 silencing enhances melanization. Conclusion There is a broad spectrum of compatibility, the extent to which the mosquito immune system limits infection, between different Plasmodium strains and particular mosquito strains that is mediated by TEP1/LRIM1 activation. The interactions between highly compatible animal models of malaria, such as P. yoelii (17XNL)-An. stephensi (Nijmegen Sda500), is more similar to that of P. falciparum (3D7)-An. gambiae (G3).