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Viruses have been demonstrated or suspected as the causative agents of various types of uveitis. Hepatitis B virus (HBV), apart from causing hepatitis, has also been implicated in the pathogenesis of systemic vasculitis, for example in glomerulonephritis and polyarteritis nodosa. It is therefore possible to postulate that a similar vasculitic process might occur in the eye leading to intraocular inflammation. A recent report from Switzerland suggests that HBV may be implicated in the aetiology of uveitis, as hepatitis B surface antigen (HBsAg) was found in the serum of 13% of cases of uveitis. Since the status of HBV in the aetiology of uveitis in Great Britain has not been investigated, we have examined serum from 200 cases of uveitis of various clinical types for the presence of circulating HBsAg. Only 4 cases (2%) were found to be HBsAg positive. This study failed, therefore, to confirm HBV as an important cause of uveitis in this country, but one cannot exclude the possibility that it may play a pathogenetic role in a small proportion of such cases.

India has committed to zero indigenous malaria cases by 2027 and elimination by 2030. Of 28 states and 8 union territories of India, eleven states were targeted to reach the elimination phase by 2020. However, state-level epidemiology indicates that several states of India may not be on the optimum track, and few goals set in National Framework for Malaria Elimination (NFME) for 2020 remain to be addressed. Therefore, tracking the current progress of malaria elimination in India at the district level, and identifying districts that are off track is important in understanding possible shortfalls to malaria elimination. Annual malaria case data from 2017-20 of 686 districts of India were obtained from the National Center for Vector-Borne Diseases Control (NCVBDC) and analysed to evaluate the performance of districts to achieve zero case status by 2027. A district's performance was evaluated by calculating the annual percentage change in the total number of malaria cases for the years 2018, 2019 and 2020 considering the previous year as a base year. The mean, median and maximum of these annual changes were then used to project the number of malaria cases in 2027. Based on these, districts were classified into four groups: 1) districts that are expected to reach zero case status by 2027, 2) districts that would achieve zero case status between 2028 and 2030, 3) districts that would arrive at zero case status after 2030, and 4) districts where malaria cases are on the rise. Analysis suggest, a cohort of fifteen districts require urgent modification or improvement in their malaria control strategies by identifying foci of infection and customizing interventions. They may also require new interventional tools that are being developed recently so that malaria case reduction over the years may be increased.

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Citation: Yadav CP, Hussain SSA, Gupta S, Bharti PK, Rahi M, Sharma A (2023) Tracking district-level performance in the context of achieving zero indigenous case status by 2027. PLOS Glob Public Health 3(1): e0001292.

Mean AROC signifies the average performance of a district over the last three years. Since there were many districts with a significant variation in annual percentages across three years, Median AROC was also calculated to deal with higher variation. Maximum AROC represents the best performance of a district in three years. Based on different AROC (mean, median, and maximum), all analysed districts of India were classified into four categories: 1) districts that would achieve zero case status by 2027, 2) districts that are expected to achieve zero cases status between 2028 and 2030), 3) districts that would achieve zero case status after 2030, and 4) districts where cases are on the increase in the last three years. Further, assuming the best-case scenario, a list of districts has been identified which may miss the malaria elimination target if necessary actions/interventions are not deployed in a timely and efficient manner. The projection of malaria cases in the year 2027 for the district was done using the below-given approach:

Similarly, the total number of years required to achieve zero case status for each of the districts can be estimated using a modified form of the compound interest equation (specified below), which was added to the base year (2020) to determine the projected year of zero case status as.

The above analysis has certain limitations which are inherent to such work. In this study, the year of achieving zero status was not predicted by developing a statistical model using advanced statistical methods (such as Generalised Liner Model (GLM), time series regression, smoothing techniques or machine learning method), as they require larger volumes of data on multiple variables (such as environmental parameters: rainfall, humidity, temperature, vegetation, differential malaria control interventions, climate zones, etc). These were not available at a granular level for all districts of India. Since no formal statistical model has been formed to predict a year of zero case status, so no validation and sensitivity analysis has been performed. Rather we have projected the number of years to reach zero case status by studying the recent progress in malaria caseload reduction via extrapolation. The data used for this study is from the public sector only and misses private sector malaria cases. The malaria surveillance in the country uses the network of health care services from primary to tertiary level and the data are collated from grassroots (village) to tertiary (district) level. However, the surveillance of the Indian malaria control programme captures ~8% of the total caseload as per World Malaria Report 2017. A substantial case burden is in the private sector (both formal and informal) which does not get reflected in the national figures [8, 9]. A large unknown caseload in the private sector could influence our findings and impact the accuracy of our analysis.

Of the 686 districts in India that were analysed, 117 districts had already achieved zero case status by 2020 or before and were therefore excluded from further analysis (Table 1 and Fig 1). From the remaining 569 districts, 205 districts reported, on an average, less than 50 cases of malaria between 2017 and 2020 and were also excluded from further analysis, assuming that these districts are likely to be on the last leg of malaria elimination. The majority of districts that have zero malaria cases or less than 50 cases on average between 2017 and 2020 belong to the northern states/UT of Jammu and Kashmir, Himachal Pradesh and Uttarakhand, northeastern states of Sikkim, Arunachal Pradesh, Manipur and Nagaland and the southern state of Tamil Nadu. Along with these, many districts from Bihar and Uttar Pradesh reported very few malaria cases, however, whether the surveillance in them was robust remains to be assessed [10].

Finally, the year of zero case status was also calculated using maximum AROC, representing the best-case scenario as it works on the maximum reduction attained by a district in the last three years. Under the best-case scenario, 335 districts were projected to achieve zero-case status by 2027. Twenty-nine districts may achieve zero malaria case status post-2027. Amongst 29 districts, 14 may achieve zero case status between 2028 to 2030 (prevention of re-establishment phase), and the remaining 15 are very crucial because they need to go beyond 2030 to achieve zero malaria case status if necessary interventions are not done on time (Table 1, Figs 1 and 2). Districts projected to fall short of the zero case status target by 2030, even under the best-case scenario, are the most vulnerable and need intense focus so that India can eliminate malaria by 2030. The fifteen districts that fall under this category are named as Dantewada, Bijapur, Narayanpur & Bastar in Chhattisgarh; West Singhbhumi in Jharkhand; Shahdol in Madhya Pradesh; Greater Mumbai and Gadhchiroli in Maharashtra; Lawangtlai & Lunglei in Mizoram; Junagadh in Gujarat; Badradri in Telangana; West Tripura in Tripura; Badaun in Uttar Pradesh and Kolkata in West Bengal (Fig 2). Amongst these districts, Greater Mumbai has the lowest AROC and the highest number of projected cases in 2027 under the best-case scenario (Fig 3). At the present pace, it is projected to report as many as 1469 malaria cases in 2027 (Fig 3), and an increment of more than 59% in AROC is needed to be able to achieve zero case status by 2027 (Fig 4). A high increment in the AROC is also needed in the districts of Lawangtlai (48.8%), Lunglei (47.8%), Dantewada (45.5%), Junagadh (39.6%), Kolkata (38.4%), Badaun (38%), Narayanpur (33.6%), Bijapur (34.7%), West Tripura (32%), Bastar (31.7%) and West Singhbhum (31%) (Fig 4). Other than these, Badaun (Uttar Pradesh) and Kolkata (West Bengal) reported the highest number of malaria cases in 2020 (11,979 and 17,032 cases respectively), such that even a relatively high rate of reduction of more than 40% may not be enough to eliminate malaria by 2027 in these districts. They are projected to report 293 and 294 cases of malaria in 2027 respectively (Fig 4).

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