Background There is a paucity of data on risk factors for infection among healthcare workers (HCWs) from India. Our objective was to evaluate the risk factors and frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among HCWs. Methods We conducted this retrospective case–control study of 3100 HCWs between May and July 2020. HCWs positive for SARS-CoV-2 infection were the cases (n=506) and those negative for SARS-CoV-2 were the controls (n=253). Univariate analysis was followed by multivariate analysis of key demographic, clinical and infection control variables. Results SARS-CoV-2 infection was found in 16.32% of HCWs. Nearly 45% of infected HCWs were asymptomatic. The proportions of sanitation workers (24% vs 8%; p<0.0001) and technicians (10% vs 4%; p=0.0002) were higher and that of doctors was lower among cases as compared with controls (23% vs 43%; p<0.0001). On univariate analysis, the type of HCW, smoking, lack of training, inadequate personal protective equipment (PPE) use and taking no or fewer doses of hydroxychloroquine (HCQ) were found to be significant. On multivariate analysis, the type of HCW (risk ratio [RR] 1.67 [95% confidence interval {CI} 1.34 to 2.08], p<0.0001), inappropriate PPE use (RR 0.63 [95% CI 0.44 to 0.89], p=0.01) and taking fewer doses of HCQ (RR 0.92 [95% CI 0.86 to 0.99], p=0.03) were significant. Conclusions The frequency of SARS-CoV-2 infection was 16% among HCWs. Being a sanitation worker, inappropriate PPE use and lack of HCQ prophylaxis predisposed HCWs to SARS-CoV-2 infection.

Various new clinical signs and symptoms, such as dysfunction of smell (anosmia) and taste (dysgeusia) have emerged ever since the coronavirus disease 2019 (COVID‐19) pandemic begun. The objective of this study was to identify the clinical presentation and factors associated with 'new loss/change of smell (anosmia) or taste (dysgeusia)' at admission in patients positive by real time polymerase chain reaction for SARS‐CoV‐2 infection. All adult COVID‐19 patients with new onset anosmia or dysgeusia at admission were included in study group. Equal number of age and gender matched COVID‐19 patients without anosmia or dysgeusia at admission were included in the control group. A total of 261 COVID‐19 patients were admitted during the study period of which 55 (21%) had anosmia and or dysgeusia. The mean (SD) age was 36 (13) years and majority were males (58%, n = 32). Comorbidity was present in 38% of cases (n = 21). Anosmia and dysgeusia were noted in more than 1/5th of the cases. Anosmia (96%, n = 53) was more common than dysgeusia (75%, n = 41). Presence of both ansomia and dysgeusia was noted in 71% of patients (n = 39). On comparing the cases with the controls, on univariate analysis, fever (higher in cases), rhinitis (lower in cases), thrombocytopenia, elevated creatinine and bilirubin (all higher in cases) were significantly associated with anosmia or dysgeusia. On multivariate analysis, only rhinitis (odds ratio [OR]: 0.28; 95% confidence interval [CI]: 0.09–0.83; p = .02) thrombocytopenia (OR: 0.99; 95% CI: 0.99–0.99; p = .01) and elevated creatinine (OR: 7.6; 95% CI: 1.5–37.6; p = .01) remained significant. In this retrospective study of COVID‐19 patients, we found anosmia and dysgeusia in more than 1/5th of the cases. Absence of rhinitis, low platelet counts and elevated creatinine were associated with anosmia or dysgeusia in these patients.

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SDN technology is becoming every day more popular and big data centers and organizational networks have started deploying for its advantages. Current development of SDN network relies on target host IP address of packet and OFSwitches ignores checking of source host IP. SDN has separated control planes and data planes and OpenFlow protocol enabled switches are used as packet forwarding devices. The SDN controller controls flow of data packet through forwarding devices and when these are turned on, do not have any control and defense. The devices are not able to handle packet arriving from connected host. In this case, data packets of hosts are sent to the controller forwarding device for inspection and control packet creation for data packet and setting up required matching entries in flow table of forwarding device for such type of data packets generated by the hosts. The attackers can generate packets with Spoofed source IP address and perform various types of attacks. In this research paper, we offer a scheme as Source IP Address Validation for Software Defined Network (SIPAV-SDN) to check packet’s source host IP address by binding source host IP Address and MAC address with switch port. It maintains a HostTable at Controller for verification of source host IP and MAC with switch port and only forwards the packets which have valid sources host IP address. We also simulated SIPAV-SDN with hybrid SDN network and experiment results have shown that it achieved 100% packet filtering accuracy for IP spoofed TCP, UDP and ICMP packet attacks. We used python programming language for RYU controller in Mininet network emulator.

SDN features are making it more popular day by day: centralized monitoring, control of network equipments, increased performance and flexibility in designing network policies as per organization requirements. The SDN controller deals with data & control plane separately. The SDN switches are simply data forwarding devices and controller decides control over forwarding data through them. Controller has a technique to identify the network switch and router nodes; but it does not identify the presence of hosts before they generated network traffic and is not able to create the packet forwarding rules, security policies. The objective of this paper is to detect connected host before they generate any traffic and store host details at controller level for future researches in area of development of new network tools, applications, optimizations techniques and security. Here, we propose Instant Detection of Host in SDN (IDH-SDN) to detect host before transmission of any data packet and store host details in a HostTable at controller level. In our experiment, various network topologies have been used to test host detection and data collection algorithm and results of all experiments verified with Wireshark network packet analyzer. The HostTable data may be used for various purposes such as development of new network tools, policies, security approaches in OpenFlow network.

Software-Defined Networking (SDN) has a detailed central model that separates the data plane from the control plane. The SDN controller is in charge of monitoring network security and controlling data flow. OpenFlow-enabled routers and switches work as packet-forwarding devices in the network system. At first, OpenFlow forwarding devices like routers and switches do not know how to handle the data packets transmitted by the host. This is because they do not have any security controls, policies, or information. These packets are sent to their destination. In this situation, the OpenFlow forwarding device sends the first data packet of a host to the SDN controller, which checks the control packets for the data packet and creates flow entries in the switch flow table to act on the following categories of data packets coming from the host. These activities at the SDN controller and switch levels are time-intensive, and the first data packet from the host always takes a longer time to reach its destination. In this article, we suggest an SDN controller with instant flow entries (SDN-CIFE) to reduce the amount of time it takes for the host to transmit its first data packet. Before traffic comes from the host, our method adds the necessary flow entries to the flow table of the OpenFlow switch. The technique was made in Python and tested on a Mininet network emulator using the RYU controller. The results of the experiment show that the time it takes to process the first data packet is reduced by more than 83%.